If you look at the UN Sustainable Development Goals, it’s clear that robots have a huge role to play in advancing the SDGs. However the field of Sustainable Robotics is more than just the application area. For every application that robotics can improve in sustainability, you have to also address the question – what are the additional costs or benefits all the way along the supply chain. What are the ‘externalities’, or additional costs/benefits, of using robots to solve the problem. Does the use of robotics bring a decrease or an increase to:

• power costs
• production costs
• labor costs
• supply chain costs
• supply chain mileage
• raw materials consumption
• and raw material choice

Solving our economic and environmental global challenges should not involve adding to the existing problems or creating new ones. So it’s important that we look beyond the first order ways in which robotics can solve global sustainable development goals and address every level at which robotics can have an impact.

Here I propose 5 levels of sustainability to frame the discussion, much as the 5 levels of autonomy have helped define the stages of autonomous mobility.

Level 1: Robots for existing recycling

Level 1 of Sustainable Robotics is simply making existing processes in sustainability more efficient, affordable and deployable. Making recycling better. Companies that are great examples are: AMP Robotics, Recycleye, MachineEx, Pellenc ST, Greyparrot, Everlast Labs and Fanuc. Here’s an explainer video from Fanuc.

“Because of AI, because of the robotic arms, we have seen plants recover 10, 20, 30% more than what they have been doing previously,” said JD Ambati, CEO of EverestLabs. “They have been losing millions of dollars to the landfill, and because of AI, they were able to identify the value of the losses and deploy robotic arms to capture that.”

Some other examples of Level 1 use robots to better monitor aquaculture, or robots to clean or install solar farms and wind turbines. If the robotics technology improves existing recycling practices then it is at Level 1 of Sustainable Robotics.

Level 2: Robots enabling new recycling

Level 2 of Sustainable Robotics is where robotics allows new materials to be recycled and in new industry application areas. A great example of this is Urban Machines, which salvages timber from construction sites and transforms it back into useable materials, something that was too difficult to do at any scale previously.

Construction using onsite materials and robotics 3D printing is another example, as seen in the NASA Habitat Challenge, sponsored by Caterpillar, Bechtel and Brick & Mortar Ventures.

Some other examples are the ocean or lake going garbage collecting robots like Waste Shark from Ran Marine, River Cleaning, or Searial Cleaners, a Quebec company whose robots were deployed in the Great Lakes Plastic Cleanup, helping to remove 74,000 plastic pieces from four lakes since 2020.

Searial Cleaners is angling for its BeBot and PixieDrone to be used as janitorial tools for beaches, marinas and golf courses, and the BeBot offers ample room for company branding. The equipment emerged from the mission of the Great Lakes Plastic Cleanup (GLPC) to harness new technologies against litter. The program also uses other devices including the Seabin, which sits in water and sucks in trash, and the Enviropod LittaTrap filter for stormwater drains.

If it’s a brand new way to practice recycling with robotic technology, then it’s at Level 2 of Sustainable Robotics.

Level 3: Robots electrifying everything

One of the biggest sustainability shifts enabled by robotics is the transition from fossil fuel powered transport, logistics and agricultural machinery into BEV, or Battery Electric Vehicle technology. On top of radically reducing emissions, the increasing use of smaller autonomous electric vehicles across first, last and middle mile can change the total number of trips taken, as well as reducing the need for large vehicles that are partially loaded taking longer trips.

Monarch Tractor’s MK-V is the world’s first electric tractor, and is ‘driver optional’, meaning it can be driven or operate autonomously, providing greater flexibility for farmers. Of course the increased use of computer vision and AI across all agrobots increase sustainability, by enabling precision or regenerative agriculture with less need for chemical solutions. Technically, these improvements to agricultural practice are Level 2 of Sustainable Robotics.

However, the use of smaller sized fully autonomous agricultural robots, such as Meropy, Burro.ai, SwarmFarm, Muddy Machines and Small Robot Company also reduces the size and soil compaction associated with agricultural machinery, and make it possible to tend smaller strip farms by machine. This is Level 3 of Sustainable Robotics.

Level 4: Robots

The higher the sustainability level, the deeper it is into the actual design and construction of the robot system. Switching to electric from fossil fuels is a small step. Switching to locally sourced or produced materials is another. Switching to recyclable materials is another step towards fully sustainable robotics.

OhmniLabs utilize 3D printing in their robot construction, allowing them to export robots to 47 countries, while also manufacturing locally in Silicon Valley.

Meanwhile, Cornell researchers Wendy Ju and Ilan Mandel have introduced the phrase ‘Garbatrage’ to describe the opportunity to prototype or build robots using components recycled from other consumer electronics, like these hoverboards.

“The time is ripe for a practice like garbatrage, both for sustainability reasons and considering the global supply shortages and international trade issues of the last few years,” the researchers said.

This is a great example of Level 4 of Sustainable Robotics.

Level 5: Self-powering/repairing Robots

Self powering or self repairing or self recycling robots are the Level 5 of Sustainable Robotics. In research, there are solutions like MilliMobile: A battery-free autonomous robot capable of operating on harvested solar and RF power. MilliMobile, developed at the Paul G. Allen School of Computer Science & Engineering, is the size of a penny and can steer itself, sense its environment, and communicate wirelessly using energy harvested from light and radio waves.

It’s not just research though. In the last two years, a number of solar powered agricultural robots have entered the market. Solinftec has a solar powered spray robot, as has EcoRobotix and AIGEN, which is also powered by wind.

Modular robotics will reduce our material wastage and energy needs by making robotics multipurpose, rather than requiring multiple specialist robots. Meanwhile self powering and self repairing technologies will allow robots to enter many previously unreachable areas, including off planet, while removing our reliance on the grid. As robots incorporate self repairing materials, the product lifecycle is increased. This is Level 5 of Sustainable Robotics.

And in the future?

While we’re waiting for the future, here are a couple of resources for turning your entire company into a sustainable robotics company. Sustainable Manufacturing 101 from ITA, the International Trade Administration and the Sustainable Manufacturing Toolkit from the OECD.

References

1. https://www.cnbc.com/2023/08/08/everestlabs-using-robotic-arms-and-ai-to-make-recycling-more-efficient.html
2. https://www.greenbiz.com/article/great-lakes-are-awash-plastic-can-robots-and-drones-help
3. https://www.economist.com/science-and-technology/2020/02/06/using-artificial-intelligence-agricultural-robots-are-on-the-rise
4. https://www.wired.co.uk/article/farming-robots-small-robot-company-tractors
5. https://news.cornell.edu/stories/2023/09/garbatrage-spins-e-waste-prototyping-gold

Researchers have come up with an innovative approach to building deformable underwater robots using simple repeating substructures. The team has demonstrated the new system in two different example configurations, one like an eel, pictured here in the MIT tow tank. Credit: Courtesy of the researchers

By David L. Chandler | MIT News Office

Underwater structures that can change their shapes dynamically, the way fish do, push through water much more efficiently than conventional rigid hulls. But constructing deformable devices that can change the curve of their body shapes while maintaining a smooth profile is a long and difficult process. MIT’s RoboTuna, for example, was composed of about 3,000 different parts and took about two years to design and build.

Now, researchers at MIT and their colleagues — including one from the original RoboTuna team — have come up with an innovative approach to building deformable underwater robots, using simple repeating substructures instead of unique components. The team has demonstrated the new system in two different example configurations, one like an eel and the other a wing-like hydrofoil. The principle itself, however, allows for virtually unlimited variations in form and scale, the researchers say.

The work is being reported in the journal Soft Robotics, in a paper by MIT research assistant Alfonso Parra Rubio, professors Michael Triantafyllou and Neil Gershenfeld, and six others.

Existing approaches to soft robotics for marine applications are generally made on small scales, while many useful real-world applications require devices on scales of meters. The new modular system the researchers propose could easily be extended to such sizes and beyond, without requiring the kind of retooling and redesign that would be needed to scale up current systems.

The deformable robots are made with lattice-like pieces, called voxels, that are low density and have high stiffness. The deformable robots are made with lattice-like pieces, called voxels, that are low density and have high stiffness. Credit: Courtesy of the researchers

“Scalability is a strong point for us,” says Parra Rubio. Given the low density and high stiffness of the lattice-like pieces, called voxels, that make up their system, he says, “we have more room to keep scaling up,” whereas most currently used technologies “rely on high-density materials facing drastic problems” in moving to larger sizes.

The individual voxels in the team’s experimental, proof-of-concept devices are mostly hollow structures made up of cast plastic pieces with narrow struts in complex shapes. The box-like shapes are load-bearing in one direction but soft in others, an unusual combination achieved by blending stiff and flexible components in different proportions.

“Treating soft versus hard robotics is a false dichotomy,” Parra Rubio says. “This is something in between, a new way to construct things.” Gershenfeld, head of MIT’s Center for Bits and Atoms, adds that “this is a third way that marries the best elements of both.”

“Smooth flexibility of the body surface allows us to implement flow control that can reduce drag and improve propulsive efficiency, resulting in substantial fuel saving,” says Triantafyllou, who is the Henry L. and Grace Doherty Professor in Ocean Science and Engineering, and was part of the RoboTuna team.

Credit: Courtesy of the researchers.

In one of the devices produced by the team, the voxels are attached end-to-end in a long row to form a meter-long, snake-like structure. The body is made up of four segments, each consisting of five voxels, with an actuator in the center that can pull a wire attached to each of the two voxels on either side, contracting them and causing the structure to bend. The whole structure of 20 units is then covered with a rib-like supporting structure, and then a tight-fitting waterproof neoprene skin. The researchers deployed the structure in an MIT tow tank to show its efficiency in the water, and demonstrated that it was indeed capable of generating forward thrust sufficient to propel itself forward using undulating motions.

“There have been many snake-like robots before,” Gershenfeld says. “But they’re generally made of bespoke components, as opposed to these simple building blocks that are scalable.”

For example, Parra Rubio says, a snake-like robot built by NASA was made up of thousands of unique pieces, whereas for this group’s snake, “we show that there are some 60 pieces.” And compared to the two years spent designing and building the MIT RoboTuna, this device was assembled in about two days, he says.

The individual voxels are mostly hollow structures made up of cast plastic pieces with narrow struts in complex shapes. Credit: Courtesy of the researchers

The other device they demonstrated is a wing-like shape, or hydrofoil, made up of an array of the same voxels but able to change its profile shape and therefore control the lift-to-drag ratio and other properties of the wing. Such wing-like shapes could be used for a variety of purposes, ranging from generating power from waves to helping to improve the efficiency of ship hulls — a pressing demand, as shipping is a significant source of carbon emissions.

The wing shape, unlike the snake, is covered in an array of scale-like overlapping tiles, designed to press down on each other to maintain a waterproof seal even as the wing changes its curvature. One possible application might be in some kind of addition to a ship’s hull profile that could reduce the formation of drag-inducing eddies and thus improve its overall efficiency, a possibility that the team is exploring with collaborators in the shipping industry.

The team also created a wing-like hydrofoil. Credit: Courtesy of the researchers

Ultimately, the concept might be applied to a whale-like submersible craft, using its morphable body shape to create propulsion. Such a craft that could evade bad weather by staying below the surface, but without the noise and turbulence of conventional propulsion. The concept could also be applied to parts of other vessels, such as racing yachts, where having a keel or a rudder that could curve gently during a turn instead of remaining straight could provide an extra edge. “Instead of being rigid or just having a flap, if you can actually curve the way fish do, you can morph your way around the turn much more efficiently,” Gershenfeld says.

The research team included Dixia Fan of the Westlake University in China; Benjamin Jenett SM ’15, PhD ’ 20 of Discrete Lattice Industries; Jose del Aguila Ferrandis, Amira Abdel-Rahman and David Preiss of MIT; and Filippos Tourlomousis of the Demokritos Research Center of Greece. The work was supported by the U.S. Army Research Lab, CBA Consortia funding, and the MIT Sea Grant Program.

• PAPER – Modular Morphing Lattices for Large-Scale Underwater Continuum Robotic Structures. Alfonso Parra Rubio, Dixia Fan, Benjamin Jenett, José del Águila Ferrandis, Filippos Tourlomousis, Amira Abdel-Rahman, David Preiss, Michael Triantafyllou, and Neil Gershenfeld. Soft Robotics (2023).

A sustainable and scalable gas fermentation technology transforms CO2 from industrial emissions into a single cell protein for animal nutrition. © Valdis Skudre, Shutterstock

By Andrew Dunne

Gardening is proven to be healthful and joyful, but as more of us discover the joys of working in the garden for the first time, some basic knowledge about plants, landscaping and soil is required to get started. What, where and when should you plant, for instance?

These were some of the core questions co-founder of the start-up Draw Me A Garden (DMAG), Florent De Salaberry, realised were standing in the way of more people digging in to the subject.

IKEA-like

Many people want to garden, but lots of us just don’t have the expertise or confidence to begin,’ said the French tech entrepreneur.

DMAG is an app and website service which offers tailored 3D-plans for garden design. It helps budding gardeners to transform any plot into a beautiful, sustainable garden with ease.

The inspiration behind the company’s name comes from the children’s book ‘Le Petit Prince’ in which the prince requests the narrator to ‘draw me a sheep’ to start a conversation and build a relationship.

De Salaberry says “Draw Me A Garden” uses digital tools in a similar way to help people build a relationship with nature in their gardens.

The DMAG service helps customers envisage their dream garden by providing creative ideas, planting tips and, most important of all, delivering all the plants to their door.

Giving customers ownership of their creations is what distinguishes DMAG from traditional landscaping, argues De Salaberry. ‘We know that if you just pay people to landscape your garden, not only is that really expensive but it’s also hard to feel pride in it,’ he said.

‘DMAG is about making gardening easy and affordable, and providing the resources to enable customers to be at the heart of their own projects.’

Garden varieties

Customers locate their garden online via a satellite map. Next, they list any pre-existing features such as a terrace or a child’s play area, then select a preferred garden style, such as for example English cottage garden or Mediterranean.

“Many people want to garden, but lots of us just don’t have the expertise or confidence to begin.”

– Florent de Salaberry, Draw Me A Garden

Behind the scenes, DMAG’s algorithm whirrs away using these inputs together with local knowledge (soil type, elevation, sun direction) to map out the perfect garden design. Customers can visualise the design using 3D mapping tools on the DMAG website.

A qualified landscaper supports the design process and the customer receives a number of planning options to mull over.

Green thumbs

Results come back almost instantaneously. ‘The idea was always to enable customers to do this wherever or whenever they wanted and it takes just a few seconds to get the first design back,’ said De Salaberry.

Once further small refinements are made, a 3D view is rendered, and customers can sit back and wait for all plants and growing instructions to be delivered.

A typical delivery might consist of between 200 – 300 plants. These come with biodegradable cardboard scaffolds cut to the exact garden size and instructions to help the gardeners plant them out.

So far, the DMAG team have supplied to gardeners of all kinds in France, Belgium and Luxembourg, with average expenditure of around €1 500.

De Salaberry likens his turnkey garden concept to how IKEA has revolutionised kitchen design.

As they look to scale-up this work in new EU countries and the US, they hope many more people will soon be asking them to start their gardening journey and “draw me a garden.”

Glade runner

If DMAG can help gardeners create the ideal future garden space, then the TrimBot2020 might be the answer to help maintain it.

The brainchild of computer vision and robotics’ expert, Professor Bob Fisher of the University of Edinburgh, TrimBot2020 is one of the first robot gardening devices that promises to do more than simply mow the lawn.

The TrimBot2020 © TrimBot2020 Consortium, 2020

Based on a modified commercially available robot lawnmower, the autonomous vehicle prunes roses, trims hedges and shapes topiary, all while auto-navigating garden terrain.

To achieve this, the robot uses a ring of cameras to draw a 3D map of the garden, some robotic snippers and hefty dose of computer processing power.

‘There are ten cameras which work together to build up a 3D model of the garden, just like our eyes do,’ said Fisher.

Together, these cameras help the robot gain a 360-degree view of the complex terrain of the garden. The robot also matches what it sees to a hand drawn map supplied by the users.

Upon command, the TrimBot springs into life by rolling up to the bush and scanning it to build up a computer-vision model of that particular plant.

‘Once it has an idea of where all the stems are, its robotic arm comes out with the cutter and it starts snipping away,’ said Fisher.

Robochop

For the TrimBot team, the commercial target market is horticultural businesses responsible for maintaining parks, gardens, and recreational areas.

In such cases, they believe the robot can take on pruning duties while the human gardener does something more challenging.

While the commercial future of TrimBot is yet to be determined, the real benefits may yet come through incorporating the technology into the “brains” of next-generation of garden robots.

‘Outdoor robotics is notoriously hard,’ said Fisher. Typical challenges include constant lighting changes, the many different shades of green and variations in the terrain.

Current robot lawnmowers usually require users to mark out an exact area to mow and to position a robot in the right place to start. TrimBot’s technology should enable robots of tomorrow to work that out themselves.

‘With the TrimBot project we’ve really demonstrated what might be possible in the future,’ said Fisher.

Research in this article was funded by the EU.

This article was originally published in Horizon, the EU Research and Innovation magazine.

Sustainable Development Goals relevant for robotics

“The use of robots responds to the UN´s call for action,” says Milton Guerry, President of the International Federation of Robotics (IFR). “The IFR supports the United Nations´ sustainable development goals. There are fantastic new ways in which robots save resources and produce green technologies of the future.”

“The transformation on the way to a sustainable use of resources is proving robotics and automation to be key technologies,” says Dr Susanne Bieller, General Secretary of the International Federation of Robotics. “Intelligent automation reduces production costs: This helps battery technology achieve a breakthrough in e-mobility for example or fuel cells production for hydrogen-power as an alternative to fossil energy. At the same time, highly efficient production technology reduces CO2-emissions.”

Clean energy, industrial innovation and sustainable agriculture are just three examples which show how the use of robots contribute to achieve these UN sustainable development goals:

Energies of the future – electricity and solar heat – Clean Energy (UN´s SDG 7)

Pivoting away from fossil fuel makes solar heat and electricity energies of the future: Solar panels are predicted to provide roughly a third of the world’s total electricity demand by 2050 – says the International Energy Agency. Heat usage makes up for half of the world’s energy usage. Keeping pace with this booming customer demand for solar panels and reflectors mean being able to produce units in greater quantities.

Solar collectors made by Absolicon © Absolicon

Industrial robots are now used as part of an automated factory production line in Sweden. Solar energy company Absolicon has developed what it sees as a gamechanger for the widespread adoption of solar heat as an energy source: A parabolic reflector focuses the solar irradiation on a receiver and turns it into steam with a temperature of up to 160 degrees for the use in industrial production. Almost all industries require heat for production processes. The solar collector´s emission-saving potential: every square meter of a solar thermal collector can produce the equivalent energy of 100 liters of oil.

ABB robot in the production line of Absolicon © ABB Robotics

The automation at Absolicon´s factory in Härnösand using two ABB robots has increased production drastically. Where the company previously produced three solar collectors per day with manual production methods, the newly installed robotic production line now has the capacity to produce a finished collector every six minutes.

“Prepare-to-repair” – Industrial Innovation (UN´s SDG 9)

Prepare-to-repair is a successful strategy for robot manufacturers and their customers to save costs and resources. This takes into account that a robot has an average service life of up to thirty years. Using less parts translating into lower risk of future failure is the first step of this approach. To offer long-term repair to customers, storage of parts is a challenge. In order to keep the large number of spare parts in stock, Japanese robot manufacturer Fanuc e.g. runs a central warehouse for Europe. It is located in Luxembourg and has the size of a football pitch with 600,000 spare parts on stock.

Since every hour of machine downtime costs the customer money, it is oftentimes more resource-efficient to transport the spare parts to the customer and repair the machine on site – rather than to manufacture and ship new machines. Manufacturers like ABB, Fanuc, KUKA or Yaskawa all run dedicated repair centers where thousands of industrial robots are refurbished and upgraded for a second life.

“Robots eliminate chemical agents” – Smart Agriculture (UN´s SDG 2)

In agriculture, new field robots eliminate the use of chemical agents. These agricultural robots travel slowly up and down the rows of crops. Equipped with cameras and artificial intelligence software, they are able to locate weeds and burn them selectively with a laser shot. The new technology does not only completely eliminate the use of herbicides. Organic farmers now have an alternative to a related process called “flaming” using propane torches to kill weeds. Flaming could only operate before crops were planted – otherwise it would also have killed the crops.

The Fraunhofer EZRT research centre and partners equipped a farming robot with navigation technology for mechanical weed control in sugar beets. The BlueBob 2.0 also does the job autonomously, so that farmers can devote their time to tasks with higher added value than manual or chemical weeding. Since manual weeding is a very tedious task for humans, the new technology also helps to improve conditions of farm work. Taking over dirty, dull and dangerous tasks is something robots excel at.

Cathy Wu is the Gilbert W. Winslow Assistant Professor of Civil and Environmental Engineering and a member of the MIT Institute for Data, Systems, and Society.

By Kim Martineau | MIT Schwarzman College of Computing

Cathy Wu is the Gilbert W. Winslow Assistant Professor of Civil and Environmental Engineering and a member of the MIT Institute for Data, Systems, and Society. As an undergraduate, Wu won MIT’s toughest robotics competition, and as a graduate student took the University of California at Berkeley’s first-ever course on deep reinforcement learning. Now back at MIT, she’s working to improve the flow of robots in Amazon warehouses under the Science Hub, a new collaboration between the tech giant and the MIT Schwarzman College of Computing. Outside of the lab and classroom, Wu can be found running, drawing, pouring lattes at home, and watching YouTube videos on math and infrastructure via 3Blue1Brown and Practical Engineering. She recently took a break from all of that to talk about her work.

Q: What put you on the path to robotics and self-driving cars?

A: My parents always wanted a doctor in the family. However, I’m bad at following instructions and became the wrong kind of doctor! Inspired by my physics and computer science classes in high school, I decided to study engineering. I wanted to help as many people as a medical doctor could.

At MIT, I looked for applications in energy, education, and agriculture, but the self-driving car was the first to grab me. It has yet to let go! Ninety-four percent of serious car crashes are caused by human error and could potentially be prevented by self-driving cars. Autonomous vehicles could also ease traffic congestion, save energy, and improve mobility.

I first learned about self-driving cars from Seth Teller during his guest lecture for the course Mobile Autonomous Systems Lab (MASLAB), in which MIT undergraduates compete to build the best full-functioning robot from scratch. Our ball-fetching bot, Putzputz, won first place. From there, I took more classes in machine learning, computer vision, and transportation, and joined Teller’s lab. I also competed in several mobility-related hackathons, including one sponsored by Hubway, now known as Blue Bike.

Q: You’ve explored ways to help humans and autonomous vehicles interact more smoothly. What makes this problem so hard?

A: Both systems are highly complex, and our classical modeling tools are woefully insufficient. Integrating autonomous vehicles into our existing mobility systems is a huge undertaking. For example, we don’t know whether autonomous vehicles will cut energy use by 40 percent, or double it. We need more powerful tools to cut through the uncertainty. My PhD thesis at Berkeley tried to do this. I developed scalable optimization methods in the areas of robot control, state estimation, and system design. These methods could help decision-makers anticipate future scenarios and design better systems to accommodate both humans and robots.

Q: How is deep reinforcement learning, combining deep and reinforcement learning algorithms, changing robotics?

A: I took John Schulman and Pieter Abbeel’s reinforcement learning class at Berkeley in 2015 shortly after Deepmind published their breakthrough paper in Nature. They had trained an agent via deep learning and reinforcement learning to play “Space Invaders” and a suite of Atari games at superhuman levels. That created quite some buzz. A year later, I started to incorporate reinforcement learning into problems involving mixed traffic systems, in which only some cars are automated. I realized that classical control techniques couldn’t handle the complex nonlinear control problems I was formulating.

Deep RL is now mainstream but it’s by no means pervasive in robotics, which still relies heavily on classical model-based control and planning methods. Deep learning continues to be important for processing raw sensor data like camera images and radio waves, and reinforcement learning is gradually being incorporated. I see traffic systems as gigantic multi-robot systems. I’m excited for an upcoming collaboration with Utah’s Department of Transportation to apply reinforcement learning to coordinate cars with traffic signals, reducing congestion and thus carbon emissions.

Q: You’ve talked about the MIT course, 6.007 (Signals and Systems), and its impact on you. What about it spoke to you?

A: The mindset. That problems that look messy can be analyzed with common, and sometimes simple, tools. Signals are transformed by systems in various ways, but what do these abstract terms mean, anyway? A mechanical system can take a signal like gears turning at some speed and transform it into a lever turning at another speed. A digital system can take binary digits and turn them into other binary digits or a string of letters or an image. Financial systems can take news and transform it via millions of trading decisions into stock prices. People take in signals every day through advertisements, job offers, gossip, and so on, and translate them into actions that in turn influence society and other people. This humble class on signals and systems linked mechanical, digital, and societal systems and showed me how foundational tools can cut through the noise.

Q: In your project with Amazon you’re training warehouse robots to pick up, sort, and deliver goods. What are the technical challenges?

A: This project involves assigning robots to a given task and routing them there. [Professor] Cynthia Barnhart’s team is focused on task assignment, and mine, on path planning. Both problems are considered combinatorial optimization problems because the solution involves a combination of choices. As the number of tasks and robots increases, the number of possible solutions grows exponentially. It’s called the curse of dimensionality. Both problems are what we call NP Hard; there may not be an efficient algorithm to solve them. Our goal is to devise a shortcut.

Routing a single robot for a single task isn’t difficult. It’s like using Google Maps to find the shortest path home. It can be solved efficiently with several algorithms, including Dijkstra’s. But warehouses resemble small cities with hundreds of robots. When traffic jams occur, customers can’t get their packages as quickly. Our goal is to develop algorithms that find the most efficient paths for all of the robots.

Q: Are there other applications?

A: Yes. The algorithms we test in Amazon warehouses might one day help to ease congestion in real cities. Other potential applications include controlling planes on runways, swarms of drones in the air, and even characters in video games. These algorithms could also be used for other robotic planning tasks like scheduling and routing.

Q: AI is evolving rapidly. Where do you hope to see the big breakthroughs coming?

A: I’d like to see deep learning and deep RL used to solve societal problems involving mobility, infrastructure, social media, health care, and education. Deep RL now has a toehold in robotics and industrial applications like chip design, but we still need to be careful in applying it to systems with humans in the loop. Ultimately, we want to design systems for people. Currently, we simply don’t have the right tools.

Q: What worries you most about AI taking on more and more specialized tasks?

A: AI has the potential for tremendous good, but it could also help to accelerate the widening gap between the haves and the have-nots. Our political and regulatory systems could help to integrate AI into society and minimize job losses and income inequality, but I worry that they’re not equipped yet to handle the firehose of AI.

Q: What’s the last great book you read?

A: “How to Avoid a Climate Disaster,” by Bill Gates. I absolutely loved the way that Gates was able to take an overwhelmingly complex topic and distill it down into words that everyone can understand. His optimism inspires me to keep pushing on applications of AI and robotics to help avoid a climate disaster.

Farming robots that can move autonomously in an open field or greenhouse promise a cleaner, safer agricultural future. But there are also potential downsides, from the loss of much-needed jobs to the safety of those working alongside the robots.

To ensure that the use of autonomous robots on farms creates more benefits than losses, a process of responsible development is required. Society as a whole needs to be involved in setting the trajectories for future farming.

We are part of a project called Robot Highways, which is currently demonstrating multiple uses for autonomous robots made by Saga Robotics on a fruit farm in south-east England. Robots are now treating plant diseases in fields and glasshouses, and will be mapping terrain, picking, packing, and providing logistical support to workers over the course of the project. This is achieved by attaching different tools to an autonomous “base robot”.

In this way, autonomous farming robots have the potential to do some of the laborious agricultural work for which farmers in some countries often struggle to find employees at a cost that keeps food prices competitive. Our project has produced an estimate that robots may eventually help reduce the number of human farm workers needed by up to 40%.

At the same time, robots could help create new jobs. The UK’s National Farmers’ Union argues that increasing use of digital technologies in farms will attract younger, skilled people to a sector struggling with an ageing workforce.

There could also be environmental benefits. Swapping traditional, fossil fuel-powered farm machinery for electric robots charged from renewable sources will cut farming’s carbon emissions. Robots equipped with ultraviolet lights that can kill mildew on plants could reduce fungicide use by up to 90%.

Machines like those produced by the Small Robot Company can navigate in tight spaces between objects like trees, so could potentially be used in agroforestry systems to perform weeding, disease treatment and mapping. They could also help reduce chemical use on farms by targeting individual plants, rather than whole fields.

However, unrestricted use of autonomous farming robots could also create problems. In parts of the world where there is not an agricultural labour shortage, reducing the demand for human workers means people will need resources and opportunities to retrain in other sectors. They may just end up moving into dull, dangerous and underpaid jobs in other industries such as mining, which will be needed to produce the materials to make the robots.

Humans who are left on the farm – or walkers on footpaths – will face health and safety concerns from having to work alongside the robots. The possibility of someone hacking a farm robot and forcing it to do their bidding cannot be overlooked. And poorer farms that can’t afford robots at all are likely to be left at a disadvantage.

There are also concerns over the ownership of the data collected by robots operated by commercial companies – and whether that data will be used for the benefit of those companies, rather than the farmers.

Responsible development

To make sure farming robots are developed responsibly, we need to get those people who might be affected by the technology –- from manufacturers and regulators to rural communities -– thinking about all its possible implications.

This might include so-called “Wizard of Oz” studies, in which remote controlled robots are tested alongside human users in order to simulate what reactions and consequences fully autonomous robots might produce once the technology is ready. This would allow robot designers to save money and manage expectations by studying user experience at the early stages of development. Another option is hosting “robot movie nights” to help show the public how robots on the farm would behave.

Once countries allow autonomous robots to be used on farms, safety and data-ownership regulations will need to be swiftly updated. In Australia, a code of practice for such robots has been developed in the crop sector and similar work is underway in the UK. This will set out robots’ obligations, state the conditions in which robots can be used, and determine who is responsible for worker and public safety.

The stakes of getting things wrong are high. Injured workers, hacked or unreliable robots, or negative consumer perception could all stand in the way of the promises of autonomous robots being realised. To help avoid this, governments can start providing rural digital and internet infrastructure, training, and financial support so that farmers can hit the ground running if autonomous robots hit the market.

Will we see autonomous robots picking fruit across Britain by 2025 – or even sooner? That depends: not on the quality of our technology alone, but also on our ability to work together to listen, learn and respond to the needs of farmers and society alike.

David Rose receives funding from UKRI (Innovate UK).

Marc Hanheide receives funding from UKRI and the EU Commission, and owns shares in SAGA Robotics.

Simon Pearson receives funding from UKRI. He is Co-Chair of the DEFRA Automation and Robotics Review for Horticulture

Original post published in The Conversation.

Autonomous and semi-autonomous trucks promise to help an industry facing a shortage of drivers and increasing e-commerce demand, but they need to demonstrate efficiency for logistics adoption. Einride AB, which has been developing electric and autonomous trucks, today launched its Intelligent Freight Mobility Platform. The system is intended to help logistics fleet managers and drivers plan routes and loads, track shipments, and monitor energy efficiency.

In February, Einride began recruiting the first remote operators for its trucks. The Stockholm-based startup also announced the beta of the Intelligent Freight Mobility Platform. In April, Einride demonstrated remote control of multiple vehicles at once.

The global market for semi-autonomous trucks will grow from 948,000 units to 3.2 million units by 2025, predicted Research and Markets. “Autonomous last-mile delivery trucks can help companies save 40% of the total cost,” and the COVID-19 pandemic is accelerating development of such technologies, said the Dublin-based firm. It also said that North America will be the largest market for autonomous trucks and Asia-Pacific will be the fastest-growing market.

Apps offer live insights for maximum efficiency

Einride said its Intelligent Freight Mobility Platform is designed to provide real-time data on loads, location data, energy usage, emissions, and more. It can provide shippers with daily freight planning through a dedicated app, intelligent routing for transport networks, and data for environmental impact auditing.

“The benefits are clear: Electric road-freight solutions account for over 90% fewer CO2 emissions and other harmful airborne pollutants, while autonomous transport is safer, more efficient, and more cost-effective,” stated Robert Falck, founder and CEO of Einride. “However, autonomous electric transport will not reach its full potential without intelligent planning and optimized vehicle networks. Our platform sets the foundation upon which the freight solutions of the future are built.”

The platform can provide specific recommendations on how to improve cost-effectiveness and sustainability with electric vehicles, according to Einride. It uses machine learning to offer implementation insights, such as how to best use existing charging infrastructure or plan new stations. The system can also make recommendations for how to optimize charging, loading, and driving schedules for maximum efficiency, said Einride.

In addition, the Intelligent Freight Mobility Platform includes an app to give drivers and operators route updates; emissions and efficiency data; and vehicle information such as charge level, range, and battery status.

“Without intelligent planning, electric and autonomous vehicles will be a patchwork solution,” said Falck. “The transport networks of the future cannot reach maximum cost and energy efficiency without recommendations on where electrification and automation will make the most impact, and how exactly to get there. That’s what our platform does for every shipment in your network.”

The Intelligent Freight Mobility Platform includes a portal to deliver live insights to fleet managers. Source: Einride

Intelligent Freight Mobility Platform works with all vehicles

The Intelligent Freight Mobility Platform can work with existing trucks, but it is optimized to work with electric and autonomous vehicles, noted Einride.

“While the platform is optimized to work with electric and autonomous vehicles outfitted with Einride-specified telematics, it is able to track, gather, and report data on any type of vehicle — diesel, electric, and/or autonomous,” a company spokeswoman told The Robot Report. “So while users will get more insights and more accurate recommendations from Einride-sourced vehicles, any future autonomous vehicle should be able to interface with our system.”

The company said trucks incorporating its system will be available from certain manufacturers, and customers such as logistics providers Lidl and Oatly will be the first to use it in Sweden.

“We are pleased with the progress our Pod has made in testing at customer sites such as with DB Schenker, and we are continuing to expand both its autonomous and remote-drive capabilities at our test sites in southern Sweden,” said the spokeswoman. “Later this year, we will have more news about our plans for the Pod.”

The post Intelligent Freight Mobility Platform designed to manage efficiency of Einride autonomous trucks appeared first on The Robot Report.

Automated, networked truck convoys could save fuel and cut down on driving time. Image credit – MAN Truck & Bus

Automation will increasingly allow vehicles to take over certain aspects of driving. However automated functions are still being fine-tuned, for example, to ensure smooth transitions when switching between the human driver and driverless mode.

Standards also need to be set across different car manufacturers, which is one of the goals of a project called L3Pilot. Although each brand can maintain some unique features, automated functions that help with navigating traffic jams, parking and motorway and urban driving must be programmed to do the same thing.

‘It’s like if you rent a car today, your expectation is that it has a gear shift, it has pedals, it has a steering wheel and so on,’ said project coordinator Aria Etemad from Volkswagen Group Research in Wolfsburg, Germany. ‘The approaches and the interfaces to the human driver are the same.’

To get the same functions from different brands to operate in an identical way, the team is creating a code of practice. This will result in a checklist for developers to run through when creating a self-driving function. ‘It’s like a cookbook for how to design and develop automated driving functions,’ said Etemad.

So far, the project team, which includes representatives from 13 vehicle manufacturers, has been conducting initial tests to make sure their company’s technology works. Cars are equipped with several sensors as well as cameras and computers which need to be properly calibrated to deal with real-world traffic.

The next step is to test the automated functions on public roads to ensure that the vehicles are ready. The tests will begin this month. Volunteer drivers will be chosen from diverse backgrounds, including different ages and genders. ‘We plan, all in all, to have 1,000 drivers using 100 vehicles in 10 different countries,’ Etemad said.

Transition

The technologies being trialled will cover a wide range of situations from overtaking on motorways to driving through urban intersections. Long journeys are also planned to see how people are able to transition back to driving after a long time in automated driving mode.

‘We really want to understand if the way we have designed our systems is the way drivers expect them to behave,’ said Etemad.

The team will also be investigating other aspects of automated driving such as the effect on traffic flow and CO2 emissions. Self-driving features are likely to make driving more efficient due to connectivity between vehicles and infrastructure, for example, although research so far has shown mixed results due to other contributing factors such as more people choosing to drive.

The first automated functions, which should be available in the next year, are likely to be for motorway driving, according to Etemad. Parking functions are likely to come to market next followed by automated urban driving, which is much more complex due to additional elements such as pedestrians and cyclists moving around.

‘There will be a good contribution from the project with results about long-term automated driving and a general understanding of people and functions that will impact how these systems are developed,’ said Etemad.

Automated functions are of interest for trucks too, where networked vehicles driving in a convoy could help save fuel, cut down on driving time or help with traffic flow. Truck platooning involves several trucks linking up through a wireless connection when they are close by so that they can share information and use automated functions to drive together as one. But so far, the concept has mostly been demonstrated in trucks of the same brand and in very few cases, with two brands.

‘Each automotive manufacturer tries it out and develops the technique within their own factory,’ said Dr Marika Hoedemaeker, a senior project manager at the Netherlands Organisation for Applied Scientific Research (TNO) in Helmond.

Truck platooning

Hoedemaeker and her project partners are now trying to break new ground by developing truck platooning that works across different brands as part of a project called ENSEMBLE. ‘Now we’re going to show that we can do this together with all the European truck manufacturers,’ said Dr Hoedemaeker.

The first phase, which the team has just completed, involved coming up with specifications that need to be implemented by all manufacturers. For example, braking and speed keeping will be automated whereas steering won’t be.

They’ve also come up with guidelines for how a convoy will respond when it enters a zone with a new speed limit or passes a toll gate, for example. ‘It’s not only communicating with the platoon but also with the outside world,’ she said.

The team is also keen to gauge the impact that a platoon will have on traffic. They would like to calculate its effect on traffic flow and whether it would in fact reduce congestion on the roads. Driving simulators will also be used to see how other drivers react when they encounter an automated truck convoy. ‘Will it change their traffic behaviour or will they never drive in the right lane anymore? There are lots of questions around this other traffic behaviour as well,’ said Dr Hoedemaeker.

Once specifications have been implemented in the trucks, they will start to test platoons on dedicated grounds then on public roads. Since trucks cross borders quite often, they will have to respect laws in different countries which vary across EU member states. The minimum following distance between vehicles, for example, differs from country to country.

In a final showcase event in May 2021, trucks from seven different brands, such as Daimler and Volvo, will drive together in one or more convoys across national borders, most likely to a key goods transport destination such as a large European port.

Following this deployment on European roads, Hoedemaeker expects the first generation platooning trucks to start being manufactured and sold a year after the project ends in 2021.

Since platoons are being developed worldwide, the standards created during the project could also be adopted more widely.

‘I think there is potential that the rest of the world could say they (Europe) already thought about the standards so we can use these and not do the whole thing over again,’ she said.

The research in this article was funded by the EU.

In a recent BBC report, “Food production accounts for one-quarter to one-third of all anthropogenic greenhouse gas emissions worldwide, and the brunt of responsibility for those numbers falls to the livestock industry.” The average US family, “emits more greenhouse gases because of the meat they eat than from driving two cars,” quipped Professor Tim Benton of the University of Leeds. “Most people don’t think of the consequences of food on climate change. But just eating a little less meat right now might make things a whole lot better for our children and grandchildren,” signed Benton.

Americans continue to chow down more than 26 billion pounds of meat a year, distressing environmentalists who assert that the current status quo is unsustainable. While veganism would provide a 70% relief to greenhouse gases worldwide, it is not foreseeable that 7 billion people would instantly change their diets to save the planet. Robotics, and even more so, artificial intelligence, is now being embraced by venture-backed entrepreneurs to artificially grow meat alternatives as creative gastronomic replacements.

Chilean startup, Not Company (NotCo), built a machine learning platform named Giuseppe to search animal ingredient substitutes. NotCo founder Matias Muchnick explains, “Giuseppe was created to understand molecular connections between food and the human perception of taste and texture.” While Muchnick did not disclose his techniques, he revealed to Business Insider that the company has hired teams of food and data scientists to classify ingredients into bits for Giuseppe. Muchnick explains the AI begins the work of processing the “data regarding how the brain works when it’s given certain flavors, when you taste salty, umami, [or] sweet.” Today, the company has a line of egg and milk alternatives on the shelves including: “Not Mayo,” Not Cheese,” “Not Yogurt and “Not Milk.” The NotCo website states that this is only the first step in a larger scheme for the deep learning algorithm: “NotCo currently has a very ambitious development plan for Giuseppe, which includes the generation of new databases with information of a different nature, such as production processes and other molecular properties of food, in such a way that Giuseppe gets closer and closer to be the most advanced chef and food scientist in the world.”

NotCo competes in a growing landscape of other animal substitute upstarts. Hampton Creek, which recently rebranded as JUST, also offers an array of dairy and egg alternatives from plant-based ingredients. The ultimate test for all these companies is creating meat in a petri dish. When responding to the challenge, JUST announced, “Through a first-of-its-kind partnership, JUST will develop cultured Wagyu beef using cells from Toriyama prized cows. Then, Awano Food Group (a premier international supplier of meat and seafood) will market and sell the meat to clients exactly how they do today with conventionally produced Toriyama Wagyu.” Today, a handful of companies, many ironically backed by livestock corporations, are also tackling the $90 billion cellular agriculture market, including: Mosa Meat, Impossible Burger, Beyond Meat, and Memphis Meats. Mosa, backed by Google founder Sergi Brin, unveiled the first synthetic burger in 2013 at a staggering cost of nearly a half million dollars.

While costs are declining, cultured meat is too expensive to supplement the American diet, especially when $1 still buys one a fast food dinner. The key to mass acceptance is attacking the largest pain point in the lab – acquiring enough genetic material from bovine tissue. Currently, the cost of such serums are close to $1,000 an ounce, and not exactly cruelty free as they are derived from animals. Many clean meat founders are proudly vegan with the implicit goal of replacing animal ingredients altogether. In order to accomplish this task, companies like JUST have invested in building robust AI and robotic systems to automatically scour the globe for plant-based alternatives. “Over 300,000 species are in the plant kingdom. That’s over 18 billion proteins, 108 million lipids, and 4 million polysaccharides. It’s an abundance almost entirely unexplored, until now,” exclaims their website. The company boasts that it is on the verge of major discoveries, “The more we explore, the more data we gather along the way. And the faster we’ll find the answers. It’s almost impossible to look at the data and say, ‘Here’s a pattern. Here’s an answer.’ So, we have to come up with algorithms to rank the materials and give downstream experiments a recommendation. In this way, we’re using data to increase the probability of discoveries.”

The next few years will unearth major breakthroughs, already Mosa announced it will have an affordable product on the shelves by 2021. To accomplish this task, the company turned to Merck’s corporate venture arm, M Ventures, and Bell Food to lead its previous  financing round. Last July, Forbes reported that the strategic partnerships are critical to Mosa’s vision in mass producing meat. According to Mosa’s founder, Mark Post, “Merck’s experience with cell cultures is very attractive from a strategic standpoint. Cell production is key to scaling cultured meat production, as they still need to figure out how to get cells to grow more rapidly and at higher numbers. In short, new technology needs to be developed. That’s where companies like Merck can lend a hand.” In addition to leveraging the conglomerates expertise in the lab, food-packaging powerhouse, Bell Food, provides a huge distribution advantage. Already, Lorenz Wyss, CEO of Bell Food Group, excitedly predicts, “Meat demand is soaring and in the future it won’t be met by livestock agriculture alone. We believe this technology can become a true alternative for environment-conscious consumers, and we are delighted to bring our know-how and expertise of the meat business into this strategic partnership with Mosa Meat.”

While the Green New Deal has been met with skepticism, the charging forces of climate change and technology are steaming ahead. Today, we have the computational and the mechatronic power to turn back the tides of destruction to implant positive change across the planet, quite possibly starting with scaling back animal agriculture. Even Winston Churchill commented in the 1931, “We shall escape the absurdity of growing a whole chicken in order to eat the breast or wing, by growing these parts separately under a suitable medium.”

Is our food source and AgTech networks under attack? Learn more at the next RobotLab on “Cybersecurity & Machines” with John Frankel of ffVC and Guy Franklin of SOSA on February 12th in New York City, RSVP Today!

]]> https://robohub.org/the-end-of-parking-as-we-know-it/ Sun, 02 Dec 2018 22:52:24 +0000 https://robohub.org/the-end-of-parking-as-we-know-it/ Read More ›]]>

A day before snow hindered New York commuters, researchers at the University of Iowa and Princeton identified the growth of urbanization as the leading cause for catastrophic storm damage. Wednesday’s report stated that the $128 billion wake of Hurricane Harvey was 21 times greater due to the population density of Houston, one of America’s fastest growing cities. This startling statistic is even more alarming in light of a recent UN study which reported that 70% of the projected 9.7 billion people in the world will live in urban centers by 2050. Superior urban management is one of the major promises of autonomous systems and smart cities.

Today, one of the biggest headaches for civil planners is the growth of traffic congestion and demand for parking, especially considering cars are one of the most inefficient and expensive assets owned by Americans. According to the Governors Highway Safety Association the average private car is parked 95% of the time. Billions of dollars of real-estate in America is dedicated to parking. For example, in a city like Seattle 40% of the land is consumed by parking. Furthermore, INRIX analytics estimates that more than $70 billion is spent by Americans looking for parking. The average driver wastes $345 a year in time, fuel and emissions. “Parking pain costs much more…New Yorkers spend 107 hours a year looking for parking spots at a cost of $2,243 per driver,” states INRIX.This month I spoke with Dr. Anuja Sonalker about her plan to save Americans billions of dollars from parking. Dr. Sonalker is the founder of STEER Technologies, a full-service auto-valet platform that is providing autonomous solutions to America’s parking pain. The STEER value proposition uses a sensor array that easily connects to a number of popular automobile models, seamlessly controlled by one’s smart phone. As Dr. Sonalker explains, “Simply put STEER allows a vehicle user to pull over at a curb (at certain destinations), and with a press of a button let the vehicle go find a parking spot and park for you. When it’s time to go, simply summon the vehicle and it comes back to get you.” An added advantage of STEER is its ability to conserve space, as cars can be parked very close together since computers don’t use doors.

Currently, STEER is piloting its technology near its Maryland headquarters. In describing her early success, Dr. Sonalker boasts, “We have successfully completed testing various scenarios under different weather, and lighting conditions at malls, train stations, airports, parks, construction sites, downtown areas. We have also announced launch dates in late 2019 with the Howard Hughes Corporation to power the Merriweather district – a 4.9 Million square foot new smart development in Columbia, MD, and the BWI airport.” The early showing from STEER’s performance is the results of its proprietary product that is built for all seasons and topographies. “Last March, we demonstrated live in Detroit under a very fast snowstorm system. Within less than an hour the ground was covered in 2+ inches of snow,” describes Dr. Sonalker. “No lane markings were visible any more, and parking lines certainly were not visible. The STEER car successfully completed its mission to ‘go park’, driving around the parking lot, recognizing other oncoming vehicles, pacing itself accordingly and locating and manoeuvring itself into a parking spot among other parked vehicles in that weather.”

In breaking down the STEER solution, Dr. Sonalker expounds, “The technology is built with a lean sensor suite, its cost equation is very favorable to both after market and integrated solutions for consumer ownership.” She further clarifies, “From a technology stand point both solutions are identical in the feature they provide. The difference lies in how the technology is integrated into the vehicle. For after market, STEER’s technology runs on additional hardware that is retrofitted to the vehicle. In an integrated solution STEER’s technology would be housed on an appropriate ECU driven by vehicle economics and architecture, but with a tight coupling with STEER’s software. The coupling will be cross layered in order to maintain the security posture.” Unlike many self-driving applications that rely heavily on LIDAR (Light Detection And Ranging), STEER uses location mapping of predetermined parking structures along with computer vision. I pressed Dr. Sonalker about her unusual setup, “Yes, it’s true we don’t use LIDAR. You see, STEER started from the principle of security-led design which is where we start from a minimum design, minimum attack surface, maximum default security.”

I continued my interview of Dr. Sonalker to learn how she plans to roll out the platform, “In the long term, we expect to be a feature on new vehicles as they roll out of the assembly line. 2020-2021 seems to be happening based on our current OEM partner targets. Our big picture vision is that people no longer have to think about what to do with their cars when they get to their destination. The equivalent effect of ride sharing – your ride ends when you get off. There will be a network of service points that your vehicle will recognize and go park there until you summon it for use again.” STEER’s solution is part of a growing fleet of new smart city initiatives cropping up across the automation landscape. At last year’s Consumer Electronic Show, German auto supplier Robert Bosch GmbH unveiled its new crowd-sourcing parking program called, “community-based parking.” Using a network of cameras and sensors to identify available parking spots Bosch’s cloud network automatically directs cars to the closest spot. This is part of Bosch’s larger urban initiative, as the company’s president Mike Mansuetti says, “You could say that our sensors are the eyes and ears of the connected city. In this case, its brain is our software. Of Bosch’s nearly 400,000 associates worldwide, more than 20,000 are software engineers, nearly 20% of whom are working exclusively on the IoT. We supply an open software platform called the Bosch IoT Suite, which offers all the functions necessary to connect devices, users, and companies.”

As the world grabbles with population explosion exacerbated by cars strangling city centers, civil engineers are challenging technologists to reimagine urban communities. Today, most cars are dormant, and when used run at one-fifth capacity with typical trips less than a mile from one’s home (easily accessible on foot or bike). In the words Dr. Sonalker, “All autonomous technologies will lead to societal change. AV Parking will result in more efficient utilization of existing spaces, fitting more in the same spaces, better use of underutilized remote lots, and frankly, even shunting parking off to further remote locations and using prime space for more enjoyable activities.”

Join the next RobotLab forum discussing “Cybersecurity & Machines” to learn how hackers are attacking the the ecosystem of smart cities and autonomous vehicles with John Frankel of ffVC and Guy Franklin of SOSA on February 12th in New York City, RSVP Today!

In many tasks in machine learning, it is common to want to answer questions given fixed, pre-collected datasets. In some applications, however, we are not given data a priori; instead, we must collect the data we require to answer the questions of interest.

This situation arises, for example, in environmental contaminant monitoring and census-style surveys. Collecting the data ourselves allows us to focus our attention on just the most relevant sources of information. However, determining which of these sources of information will yield useful measurements can be difficult. Furthermore, when data is collected by a physical agent (e.g. robot, satellite, human, etc.) we must plan our measurements so as to reduce costs associated with the motion of the agent over time. We call this abstract problem embodied adaptive sensing.

We introduce a new approach to the embodied adaptive sensing problem, in which a robot must traverse its environment to identify locations or items of interest. Adaptive sensing encompasses many well-studied problems in robotics, including the rapid identification of accidental contamination leaks and radioactive sources, and finding individuals in search and rescue missions. In such settings, it is often critical to devise a sensing trajectory that returns a correct solution as quickly as possible.

We focus on the problem of radioactive source-seeking (RSS), in which a UAV must identify the $k$-largest radioactive emitters in its environment, where $k$ is a user-defined parameter. RSS is a particularly interesting instance of the adaptive sensing problem, due both to the challenges posed by the highly heterogeneous background noise, as well as to the existence of a well-characterized sensor model amenable to the construction of statistical confidence intervals.

We introduce AdaSearch, a successive-elimination framework for general adaptive sensing problems, and demonstrate it within the context of radioactive source seeking. AdaSearch explicitly maintains confidence intervals over the emissions rate at each point in the environment. Using these confidence intervals, the algorithm iteratively identifies a set of candidate points likely to be among the top emitters, and eliminates other points.

Embodied Search as a Multiple Hypothesis Testing Scenario

Traditionally, the robotics community has conceived of embodied search as a continuous motion planning problem, where the robot must balance exploring its environment with selecting efficient trajectories. This has motivated approaches where both trajectory optimization and exploration are combined into a single objective, which can be optimized using receding horizon control (Hoffman and Tomlin, Bai et al., Marchant and Ramos). Instead, we consider an alternate approach in which we formulate the problem as one of sequential best-action identification via hypothesis testing.

In sequential hypothesis testing, the goal is to reach conclusions on many separate questions, by iteratively collecting data. An agent is given a set of $N$ measurement actions, each of which yields observations according to a distinct, fixed distribution.

The agent’s goal is to learn some prespecified property of these $N$ observation distributions. For example, in a statistical “A/B test,” a measurement action corresponds to showing a new customer either product A or product B, and recording their assessment of that product. Here, $N=2$ because there are just two actions, showing product A and showing product B. The property of interest is which product is preferred on average (B in the illustration below). As we collect measurements on preferences, we keep track of sample averages, as well as confidence intervals around them, described by a lower confidence bound (LCB) and an upper confidence bound (UCB) for each product. As we collect more measurements, we become more confident in our estimate of preference for each individual product, and therefore our ranking between products. This suggests a condition for concluding that product B is preferred to product A: If the LCB for product B is greater than the UCB for product A, then we can conclude that with high probability, B is prefered to A, on average.

In the context of environmental sensing, each action may correspond to taking a sensor reading from a given position and orientation. Typically, the agent wishes to know which single measurement action yields observations with the greatest mean observed signal, or which set of $k$ actions together have the greatest mean observations. To do so, the agent may choose actions sequentially, using previously measured observations to favor future actions which are most informative for discerning the actions with largest mean observations.

At first glance, sequential best-action identification may seem like too abstract a framework to be useful in mobile, embodied sensing agents. Indeed, the agent can choose any arbitrary sequence of measurement actions, without considering the potential costs—such as movement time—associated with changing actions. However, the abstract nature of sequential best-action identification is also its most formidable strength. By formulating the embodied search problem in precise statistical language, we develop actionable confidence intervals about the observation means associated with each sensing action, and determine the set of all actions which still need to be taken before the points of interest can confidently determined.

Our proposed approach to embodied search, AdaSearch, uses confidence intervals from sequential best-action identification and a global trajectory planning heuristic to both achieve asymptotically optimal measurement complexity, and effectively amortize movement costs.

Radioactive Source Seeking

For concreteness, we will present AdaSearch in the context of the radioactive source seeking problem with a single source. We model the environment as a planar grid, as in the depiction below. There is exactly one high-intensity radioactive point source (red dot). However, locating this source is difficult because sensor measurements are corrupted by the background radiation (pink dots). Sensor measurements are obtained by flying a quadrotor equipped with a radiation sensor above the grid. The goal is to devise a sequence of trajectories so that the measurements obtained from the onboard sensor allow us to disambiguate the radioactive point source from the background radiation sources, as quickly as possible.

AdaSearch

Our algorithm, AdaSearch, combines a global-coverage planning approach with an adaptive sensing rule based on hypothesis testing to define these trajectories. In the first pass through the grid, we sample uniformly over the environment.

After observing the measurements during the first pass, we can eliminate some regions from consideration. Points are eliminated if the upper bound of our estimated confidence interval around their mean is smaller than the largest lower bound of any interval. This means that with high probability, they are not the source that we’re looking for.

In the next round, AdaSearch focuses on sampling the remaining points (teal squares) more carefully, because they are still potential source locations.

This process continues, and with each round the set of candidate source locations shrinks until only a single point remains. AdaSearch returns this point (enlarged red point) as the radioactive point source we were searching for.

Due to the crisp statistical formulation of confidence, we can be sure that under known sensing models, AdaSearch returns the correct source with high probability. We ensure a certain level of confidence in this probabilistic guarantee by fixing the width (in standard deviations) of the confidence bounds around each individual region, throughout the course of the algorithm. Furthermore, AdaSearch comes with environment-specific runtime guarantees, as we describe in detail in our paper.

Baselines

Perhaps the most popular approach for general adaptive search problems is information maximization (Bourgault et al.). Information maximization methods collect measurements in locations deemed promising according to an information theoretic criterion, and follow a receding horizon strategy to plan trajectories. We compare AdaSearch to a version of information maximization tailored to radiation detection: InfoMax.

Unfortunately, for large search spaces, the real-time computational constraints of this approach necessitate approximations such as limits on planning horizon and trajectory parameterization. These approximations may cause the algorithm to be excessively greedy and spend too much time tracking down false leads.

To disambiguate between the effects of our statistical confidence intervals and global planning heuristic (vs. InfoMax’s information metric and receding horizon planning), we implement as a simple global planning approach, NaiveSearch, as a second baseline. This approach samples the grid uniformly, spending an equal amount of time at each grid cell.

Results

We implemented all three algorithms and simulated their performance on ten randomized instantiations of the problem on a 64 by 64 meter grid, at 4 meter resolution, using realistic quadrotor dynamics and simulated radiation sensor readings.

In our experiments, we observe that AdaSearch usually finishes faster than NaiveSearch and InfoMax. As we increase the maximum background radiation level, the ratio of AdaSearch’s run time to NaiveSearch’s runtime continues to improve, which matches the theoretical bounds given in the full paper.

The increase in performance between AdaSearch and NaiveSearch suggests that adaptivity does confer advantages over non-adaptive methods. Even more strikingly, and somewhat unexpectedly, even NaiveSearch tends to outperform InfoMax in this problem setting. This suggests that the locally greedy nature of receding horizon control in InfoMax is indeed hurting its performance. AdaSearch, by contrast, gracefully blends adaptive strategies with global coverage guarantees.

AdaSearch more generally

The successful demonstration of AdaSearch operating onboard a UAV in the context of finding radioactive sources prompts us to ask, in what more general problem settings will AdaSearch also perform well? As it turns out, the core algorithm applies more broadly, even to non-robotic embodied sensing problems.

For example, consider the problem of planning a pilot program at 10 out of 100 medical clinics spread across a region. We might wish to establish these programs in the locations with the highest rates of a particular rare disease by conducting surveys across potential clinic locations to assess rates of illness in each region. This is an embodied sensing problem, as diagnoses are made in person. Resources are limited in terms of the number of human surveyors, and there are physical constraints both on the time required to survey a group of people, and on the travel time between towns.

A survey planner could use AdaSearch to guide the decisions of how long to spend in each potential clinic location counting new cases of the disease before moving on to the next, and to trade-off the travel time of returning to collect more data from a certain town with spending extra time at the town in the first place.

In general, AdaSearch is expected to perform well when we think that measurements are noisy enough to warrant multiple passes through space when collecting data. Radioactive gamma ray emissions, as well as occurances of a rare disease, can be modeled as Poisson distributed random variables, where the variance scales with the mean. AdaSearch easily adapts to different noise models (e.g. Gaussian), which might arise with different applications. So long as we can calculate or bound the appropriate confidence intervals, AdaSearch guarantees an efficient traversal of the region to find the points of interest.

For more information about AdaSearch, please see full video at the top of the page, and the full text of the paper at: https://arxiv.org/abs/1809.10611. This article was initially published on the BAIR blog, and appears here with the authors’ permission.

An aqua drone developed by the WasteShark project can collect litter in harbors before it gets carried out into the open sea. Image credit – WasteShark

The cost of sea litter in the EU has been estimated at up to €630 million per year. It is mostly composed of plastics, which take hundreds of years to break down in nature, and has the potential to affect human health through the food chain because plastic waste is eaten by the fish that we consume.

‘I’m an accidental environmentalist,’ said Richard Hardiman, who runs a project called WASTESHARK. He says that while walking at his local harbour one day he stopped to watch two men struggle to scoop litter out of the sea using a pool net. Their inefficiency bothered Hardiman, and he set about trying to solve the problem. It was only when he delved deeper into the issue that he realised how damaging marine litter, and plastic in particular, can be, he says.

‘I started exploring where this trash goes – ocean gyres (circular currents), junk gyres, and they’re just full of plastic. I’m very glad that we’re now doing something to lessen the effects,’ he said.

Hardiman developed an unmanned robot, an aqua drone that cruises around urban waters such as harbours, marinas and canals, eating up marine litter like a Roomba of the sea. The waste is collected in a basket which the WasteShark then brings back to shore to be emptied, sorted and recycled.

The design of the autonomous drone is modelled on a whale shark, the ocean’s largest known fish. These giant filter feeders swim around with their mouths open and lazily eat whatever crosses their path.

It’s powered by rechargeable electric batteries, ensuring that it doesn’t pollute the environment through oil spillage or exhaust fumes, and it is relatively silent, avoiding noise pollution. It produces zero carbon emissions and the device moves quite slowly, allowing fish and birds to merely swim away when it gets too close for comfort.

‘We’ve tested it in areas of natural beauty and natural parks where we know it doesn’t harm the wildlife,’ said Hardiman. ‘We’re quite fortunate in that, all our research shows that it doesn’t affect the wildlife around.’

#WasteShark chomping floating plastic! #Turnthetideonoplastic #plasticfree #plasticpollution #Plasticsoup pic.twitter.com/zgnKEutWGX

— RanMarine Technology (@RanMarineTech) January 26, 2018

WasteShark’s autonomous drone is modelled on a whale shark. Credit – RanMarine Technology

WasteShark is one of a number of new inventions designed to tackle the problem of marine litter. A project called CLAIM is developing five different kinds of technology, one of which is a plasma-based tool called a pyrolyser. 

Useful gas

CLAIM’s pyrolyser will use heat treatment to break down marine litter to a useful gas. Plasma is basically ionised gas, capable of reaching very high temperatures of thousands of degrees. Such heat can break chemical bonds between atoms, converting waste into a type of gas called syngas.

The pyrolyser will be mounted onto a boat collecting floating marine litter – mainly large items of plastic which, if left in the sea, will decay into microplastic – so that the gas can then be used as an eco-friendly fuel to power the boat, or to provide energy for heating in ports.

Dr Nikoleta Bellou of the Hellenic Centre for Marine Research, one of the project coordinators of CLAIM, said: ‘We know that we humans are actually the key drivers for polluting our oceans. Unlike organic material, plastic never disappears in nature and it accumulates in the environment, especially in our oceans. It poses a threat not only to the health of our oceans and to the coasts but to humans, and has social, economic and ecological impacts.’

The researchers chose areas in the Mediterranean and Baltic Seas to act as their case studies throughout the project, and will develop models that can tell scientists which areas are most likely to become litter hotspots. A range of factors influence how littered a beach may be – it’s not only affected by litter louts in the surrounding area but also by circulating winds and currents which can carry litter great distances, dumping the waste on some particular beaches rather than others.

CLAIM’s other methods to tackle plastic pollution include a boom – a series of nets criss-crossing a river that catches all the large litter that would otherwise travel to the sea. The nets are then emptied and the waste is collected for treatment with the pyrolyser. There have been problems with booms in the past, when bad weather conditions cause the nets to overload and break, but CLAIM will use automated cameras and other sensors that could alert relevant authorities when the nets are full.

Microplastics

Large plastic pieces that can be scooped out of the water are one thing, but tiny particles known as microplastics that are less than 5mm wide pose a different problem. Scientists on the GoJelly project are using a surprising ingredient to create a filter that prevents microplastics from entering the sea – jellyfish slime.

The filter will be deployed at waste water management plants, a known source of microplastics. The method has already proven to be successful in the lab, and now GoJelly is planning to upscale the biotechnology for industrial use.

Dr Jamileh Javidpour of the GEOMAR Helmholtz Centre for Ocean Research Kiel, who coordinates the project, said: ‘We have to be innovative to stop microplastics from entering the ocean.’

The GoJelly project kills two birds with one stone – tackling the issue of microplastics while simultaneously addressing the problem of jellyfish blooms, where the creatures reproduce in high enough levels to blanket an area of ocean.

Jellyfish are one of the most ancient creatures on the planet, having swum in Earth’s oceans during the time of the dinosaurs. On the whole, due to a decline in natural predators and changes in the environment, they are thriving. When they bloom, jellyfish can attack swimmers and fisheries.

Fishermen often throw caught jellyfish back into the sea as a nuisance but, according to Dr Javidpour, jellyfish can be used much more sustainably. Not only can their slime be used to filter out microplastics, they can also be used as feed for aquaculture, for collagen in anti-ageing products, and even in food.

In fact, part of the GoJelly project involves producing a cookbook, showing people how to make delicious dishes from jellyfish. While Europeans may not be used to cooking with jellyfish, in many Asian cultures they are a daily staple. However, Dr Javidpour stresses that the goal is not to replace normal fisheries.

‘We are mainly ecologists, we know the role of jellyfish as part of a healthy ecosystem,’ she said. ‘We don’t want to switch from classical fishery to jellyfish fishery, but it is part of our task to investigate if it is doable, if it is sustainable.’

The research in this article has been funded by the EU.

]]> https://robohub.org/self-driving-cars-have-power-consumption-problems/ Thu, 08 Mar 2018 22:38:59 +0000 http://robohub.org/self-driving-cars-have-power-consumption-problems/

I recently chaired a UJA Tech Talk on “The Future Of Autonomous Cars” with former General Motors Vice-Chairman Steve Girsky. The auto executive enthusiastically shared his vision for the next 15-25 years of driving – a congestion-free world of automated wheeled capsules zipping commuters to and from work.

Girsky stated that connected cars with safety assist (autonomy-lite) features are moving much faster toward mass adoption than fully autonomous vehicles (sans steering wheels and pedals). In his opinion, the largest roadblocks toward a consumer-ready robocar are the current technical inefficiencies of prototypes on the road today, which burn huge amounts of energy supporting enhanced computing and arrays of sensors. This makes the sticker price closer to a 1972 Ferrari than a 2018 Prius.

As main street adoption relies heavily on converting combustion engines to electric at accessible pricing, Girsky’s sentiment was shared by many CES 2018 participants. NVIDIA, the leading chip manufacturer for autonomous vehicles, unveiled its latest technology, Xavier, with auto industry partner Volkswagen in Las Vegas. Xavier promises to be 15 times more energy-efficient than previous chip generations delivering 30 trillion operations per second by wielding only 30 watts of power.

After the Xavier CES demonstration, Volkswagen CEO Herbert Diess exclaimed, “Autonomous driving, zero-emission mobility, and digital networking are virtually impossible without advances in AI and deep learning. Working with NVIDIA, the leader in AI technology, enables us to take a big step into the future.”

NVIDIA is becoming the industry standard as Volkswagen joins more than 320 companies and organizations working with the chip manufacturer on autonomous vehicles. While NVIDIA is leading the pack, Intel and Qualcomm are not far behind with their low-power solutions. Electric vehicle powerhouse Tesla is developing its own internal chip for the next generation of Autopilot. While these new chips represents a positive evolution in processors, there is still much work to be done as current self-driving prototypes require close to 2,500 watts per second.

Power Consumption a Tradeoff for Self-Driving Cars

The power-consumption problem was highlighted recently with a report published by the the University of Michigan Center for Sustainable Systems. Its lead author, Greg Keoleian, questions whether the current autonomous car models will slow the overall adoption towards electric vehicles. Keoleian’s team simulated a number of self-driving Ford Fusion models with different-sized computer configurations and engine designs. In sharing his findings, Keoleian said, “We knew there was going to be a tradeoff in terms of the energy and greenhouse gas emissions associated with the equipment and the benefits gained from operational efficiency. I was surprised that it was so significant.”

Keoleian’s conclusions challenged the premise of self-driving cars accelerating the adoption of renewal energy. For years, the advocates of autonomous vehicles have claimed that smart driving will lead to a reduction of greenhouse gas emissions through the platooning of vehicles on highways and intersections; the decrease of aerodynamic drag on freeways, and the overall reduction in urban congestion.

Analysis: How California’s Self-Driving Cars Performed in 2017

However, the University of Michigan tests only showed a “six to nine percent net energy reduction” over the vehicle’s lifecycle when running on autonomy mode. This went down by five percent when using a large Waymo rooftop sensor package (shown below) as it increased the aerodynamic drag. The report also stated that the greatest net efficiencies were in cars with gas drivetrains that benefit the most from smart driving. Waymo currently uses a hybrid Chrysler Pacifica to run its complex fusion of sensors and processing units.

Keoleian told IEEE Spectrum that his modeling actually “overstates real impacts from future autonomous vehicles.” While he anticipates the reduction of computing and sensor drag, he is concerned that the impact of 5G communications has not been fully explored. The increased bandwidth will lead to greater data streams and boost power consumption for inboard systems and processors. In addition, he thinks that self-driving systems will lead to greater distances traveled as commuters move further away from city centers with the advent of easier commutes. Keoleian explains, “There could be a rebound effect. They could induce travel, adding to congestion and fuel use.” Koeleian points to a confusing conclusion by the U.S. National Renewable Energy Laboratory that presents two possible outcomes of full autonomy:

1. A reduction in greenhouse emissions by sixty percent with greater ride sharing options
2. An increase of two hundred percent with increased driving distances

According to Wilko Stark, Mercedes-Benz’s Vice President of Strategy, it only makes sense for autonomous vehicles to be electric as the increased power requirements will go to the computers instead of the motors. “To put such a system into a combustion-engined car doesn’t make any sense, because the fuel consumption will go up tremendously,” explains Stark.

Analysis: Fleet Expansion Shows Waymo Lapping Self-Driving Competition

Girsky shares Stark’s view, as he predicted that the first large scale use cases for autonomy will be fleets of souped-up golf carts running low speed pre-planned shuttle routes. Also on view at CES were complimentary autonomous shared taxi rides around Las Vegas, courtesy of French startup Navya. Today, Navya boasts of 60 operating shuttles in more than 10 cities, including around the University of Michigan.

Fully autonomous cars might not be far behind, as Waymo has seen a ninety percent drop in component costs by bringing its sensor development in-house. The autonomous powerhouse recently passed the four million mile marker on public roads and is planning on ditching its safety driver later this year in its Phoenix, Arizona test program. According Dmitri Dolgov, Vice President of Waymo’s Engineering, “Sensors on our new generation of vehicles can see farther, sharper, and more accurately than anything available on the market. Instead of taking components that might have been designed for another application, we engineered everything from the ground up, specifically for the task of Level 4 autonomy.”

With increased roadside fatalities and rising CO2 emissions, the world can’t wait too much longer for affordable, energy-efficient autonomous transportation. Girsky and others remind us there is still a long road ahead, while the industry experts estimate that the current gas-burning Waymo Chrysler Pacifica cruising around Arizona costs more than one hundred times the sticker price of the minivan. I guess until then there is always Citibike.

]]> https://robohub.org/why-ethical-robots-might-not-be-such-a-good-idea-after-all/ Thu, 08 Feb 2018 22:30:00 +0000 http://robohub.org/why-ethical-robots-might-not-be-such-a-good-idea-after-all/ Last week my colleague Dieter Vanderelst presented our paper: The Dark Side of Ethical Robots at AIES 2018 in New Orleans.

I blogged about Dieter’s very elegant experiment here, but let me summarise. With two NAO robots he set up a demonstration of an ethical robot helping another robot acting as a proxy human, then showed that with a very simple alteration of the ethical robot’s logic it is transformed into a distinctly unethical robot – behaving either competitively or aggressively toward the proxy human.

Here are our paper’s key conclusions:

The ease of transformation from ethical to unethical robot is hardly surprising. It is a straightforward consequence of the fact that both ethical and unethical behaviours require the same cognitive machinery with – in our implementation – only a subtle difference in the way a single value is calculated. In fact, the difference between an ethical (i.e. seeking the most desirable outcomes for the human) robot and an aggressive (i.e. seeking the least desirable outcomes for the human) robot is a simple negation of this value.

On the face of it, given that we can (at least in principle) build explicitly ethical machines then it would seem that we have a moral imperative to do so; it would appear to be unethical not to build ethical machines when we have that option. But the findings of our paper call this assumption into serious doubt. Let us examine the risks associated with ethical robots and if, and how, they might be mitigated. There are three.

1. First there is the risk that an unscrupulous manufacturermight insert some unethical behaviours into their robots in order to exploit naive or vulnerable users for financial gain, or perhaps to gain some market advantage (here the VW diesel emissions scandal of 2015 comes to mind). There are no technical steps that would mitigate this risk, but the reputational damage from being found out is undoubtedly a significant disincentive. Compliance with ethical standards such as BS 8611 guide to the ethical design and application of robots and robotic systems, or emerging new IEEE P700X ‘human’ standards would also support manufacturers in the ethical application of ethical robots. 
2. Perhaps more serious is the risk arising from robots that have user adjustable ethics settings. Here the danger arises from the possibility that either the user or a technical support engineer mistakenly, or deliberately, chooses settings that move the robot’s behaviours outside an ‘ethical envelope’. Much depends of course on how the robot’s ethics are coded, but one can imagine the robot’s ethical rules expressed in a user-accessible format, for example, an XML like script. No doubt the best way to guard against this risk is for robots to have no user adjustable ethics settings, so that the robot’s ethics are hard-coded and not accessible to either users or support engineers. 
3. But even hard-coded ethics would not guard against undoubtedly the most serious risk of all, which arises when those ethical rules are vulnerable to malicious hacking. Given that cases of white-hat hacking of cars have already been reported, it’s not difficult to envisage a nightmare scenario in which the ethics settings for an entire fleet of driverless cars are hacked, transforming those vehicles into lethal weapons. Of course, driverless cars (or robots in general) without explicit ethics are also vulnerable to hacking, but weaponising such robots is far more challenging for the attacker. Explicitly ethical robots focus the robot’s behaviours to a small number of rules which make them, we think, uniquely vulnerable to cyber-attack.

Ok, taking the most serious of these risks: hacking, we can envisage several technical approaches to mitigating the risk of malicious hacking of a robot’s ethical rules. One would be to place those ethical rules behind strong encryption. Another would require a robot to authenticate its ethical rules by first connecting to a secure server. An authentication failure would disable those ethics, so that the robot defaults to operating without explicit ethical behaviours. Although feasible, these approaches would be unlikely to deter the most determined hackers, especially those who are prepared to resort to stealing encryption or authentication keys.

It is very clear that guaranteeing the security of ethical robots is beyond the scope of engineering and will need regulatory and legislative efforts. Considering the ethical, legal and societal implications of robots, it becomes obvious that robots themselves are not where responsibility lies. Robots are simply smart machines of various kinds and the responsibility to ensure they behave well must always lie with human beings. In other words, we require ethical governance, and this is equally true for robots with or without explicit ethical behaviours.

Two years ago I thought the benefits of ethical robots outweighed the risks. Now I’m not so sure. I now believe that – even with strong ethical governance – the risks that a robot’s ethics might be compromised by unscrupulous actors are so great as to raise very serious doubts over the wisdom of embedding ethical decision making in real-world safety critical robots, such as driverless cars. Ethical robots might not be such a good idea after all.

Here is the full reference to our paper:

Vanderelst D and Winfield AFT (2018), The Dark Side of Ethical Robots, AAAI/ACM Conf. on AI Ethics and Society (AIES 2018), New Orleans.

]]> https://robohub.org/robocars-will-make-traffic-worse-before-it-gets-better/ Wed, 25 Oct 2017 21:08:14 +0000 http://robohub.org/robocars-will-make-traffic-worse-before-it-gets-better/

Many websites paint a very positive picture of the robocar future. And it is positive, but far from perfect. One problem I worry about in the short term is the way robocars are going to make traffic worse before they get a chance to make it better.

The goal of all robocars is to make car travel more pleasant and convenient, and eventually cheaper. You can’t make something better and cheaper without increasing demand for it, and that means more traffic.

This is particularly true for the early-generation pre-robocar vehicles in the plans of many major automakers. One of the first products these companies have released is sometimes called the “traffic jam assist.” This is a self-driving system that only works at low speed in a traffic jam.

Turns out that’s easy to do, effectively a solved problem. Low speed is inherently easier, and the highway is a simple driving environment without pedestrians, cyclists, intersections or cars going the other way. When you are boxed in with other cars in a jam, all you have to do is go with the flow. The other cars tell you where you need to go. Sometimes it can be complex when you get to whatever is blocking the road to cause the jam, but handoff to a human at low speeds is also fairly doable.

These products will be widely available soon, and they will make traffic jams much more pleasant. Which means there might be more of them.

I don’t have a 9 to 5 job, so I avoid travel in rush hour when I can. If somebody suggests we meet somewhere at 9am, I try to push it to 9:30 or 10. If I had a traffic jam assist car, I would be more willing to take the meeting at 9. When on the way, if I encountered a traffic jam, I would just think, “Ah, I can get some email done.”

After the traffic jam assist systems, come the highway systems which allow you to take your eyes off the road for an extended time. They arrive pretty soon, too. These will encourage slightly longer commutes. That means more traffic, and also changes to real estate values. The corporate-run commuter buses from Google, Yahoo and many other tech companies in the SF Bay Area have already done that, making people decide they want to live in San Francisco and work an hour’s bus ride away in Silicon Valley. The buses don’t make traffic worse, but those doing this in private cars will.

Is it all doom?

Fortunately, some factors will counter a general trend to worse traffic, particularly as full real robocars arrive, the ones that can come unmanned to pick you up and drop you off.

• As robocars reduce accident levels, that will reduce one of the major causes of traffic congestion.
• Robocars don’t need to slow down and stare at accidents or other unusual things on the road, which also causes congestion.
• Robocars won’t overcompensate on “sags” (dips) in the road. This overcompensation on sags is the cause of almost half the traffic congestion on Japanese highways
• Robocars look like they’ll be mainly electric. That doesn’t do much about traffic, but it does help with emissions.
• Short-haul “last mile” robocars can actually make the use of trains, buses and carpools vastly more convenient.
• Having only a few cars which drive more regularly, even something as simple as a good quality adaptive cruise control, actually does a lot to reduce congestion.
• The rise of single person half-width vehicles promises a capacity increase, since when two find one another on the road, they can share the lane.
• While it won’t happen in the early days, eventually robocars will follow the car in front of them with a shorter gap if they have a faster reaction time. This increases highway capacity.
• Early robocars won’t generate a lot of carpooling, but it will pick up fairly soon (see below.)

What not to worry about

There are a few nightmare situations people have talked about that probably won’t happen. Today, a lot of urban driving involves hunting for parking. If we do things right, robocars won’t ever hunt for parking. They (and you) will be able to make an online query for available space at the best price and go directly do it. But they’ll do that after they drop you off, and they don’t need to park super close to your destination the way you need to. To incorporate city spaces into this market, a technology upgrade will be needed, and that may take some time, but private spaces can get in the game quickly.

What also won’t happen is people telling their car to drive around rather than park, to save money. Operating a car today costs about $20/hour, which is vastly more than any hourly priced parking, so nobody is going to do that to save money unless there is literally no parking for many miles. (Yes, there are parking lots that cost more than $20, but that’s because they sell you many hours or a whole day and don’t want a lot of in and out traffic. Robocars will be the most polite parking customers around, hiding valet-style at the back of the lot and leaving when you tell them.)

Another common worry is that people will send their cars on long errands unmanned. That mom might take the car downtown, and send it all the way back for dad to do a later commute, then back to pickup the kids at school. While that’s not impossible, it’s actually not going to be the cheap or efficient thing to do. Thanks to robotaxis, we’re going to start thinking of cars as devices that wear out by the mile, not by the year, and all their costs will be by the mile except parking and $2 of financing per day. All this unmanned operation will almost double the cost of the car, and the use of robotic taxi services (Robocar Uber) will be a much better deal.

There will be empty car moves, of course. But it should not amount to more than 15% of total miles. In New York, taxis are vacant of a passenger for 38% of miles, but that’s because they cruise around all day looking for fares. When you only move when summoned, the rate is much better.

And then it gets better

After this “winter” of increased traffic congestion, the outlook gets better. Aside from the factors listed above, in the long term we get the potential for several big things to increase road capacity.

The earliest is dynamic carpooling, as you see with services like UberPool and LyftLines. After all, if you look at a rush-hour highway, you see that most of the seats going by are empty. Tools which can fill these seats can increase the capacity of the roads close to three times just with the cars that are moving today.

The next is advanced robocar transit. The ability to make an ad-hoc, on-demand transit system that combines vans and buses with last mile single person vehicles in theory allows almost arbitrary capacity on the roads. At peak hours, heavy use of vans and buses to carry people on the common segments of their routes could result in a 10-fold (or even more) increase in capacity, which is more than enough to handle our needs for decades to come.

Next after that is dynamic adaptation of roads. In a system where cities can change the direction of roads on demand, you can get more than a doubling of capacity when you combine it with repurposing of street parking. On key routes, street parking can be reserved only for robocars prior to rush hour, and then those cars can be told they must leave when rush hour begins. (Chances are they want to leave to serve passengers anyway.) Now your road has seriously increased capacity, and if it’s also converted to one-way in the peak direction, you could almost quadruple it.

The final step does not directly involve robocars, since all cars must have a smartphone and participate for it to work. This is the use of smart, internet based road metering. With complete metering, you never get more cars trying to use a road segment than it has capacity to handle, and so you very rarely get traffic congestion. You also don’t get induced demand that is greater than the capacity, solving the bane of transportation planners.

]]> https://robohub.org/the-drone-centers-weekly-roundup-71717/ Tue, 18 Jul 2017 19:05:35 +0000 http://robohub.org/the-drone-centers-weekly-roundup-71717/ Read more →

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The South Korean Navy conducted shipboard flight tests for the TR-60 tilt-rotor UAV. Source: KARI

July 10, 2017 – July 16, 2017

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News

A U.S. drone strike in Afghanistan killed Abu Sayed, the leader of the local ISIS cell. In a statement, a Pentagon spokesperson said that the strike targeted the ISIS headquarters in Kunar Province. Abu Sayed’s predecessor, Abdul Hasib, was killed in a special forces raid in April. (New York Times)

A Turkish drone strike in Anatolia reportedly killed five suspected members of the Kurdistan Workers’ Party. It was the first strike carried out with the Anka-S, a new Turkish surveillance and strike drone. (IHS Jane’s Defense Weekly)

Portugal will implement a new law regulating drone operations after a recent spike in reports of close encounters between drones and manned aircraft. Drone users will be required to register and purchase insurance. Speaking with members of a parliamentary committee, Infrastructure Minister Pedro Marques said that he hopes the law will be in place by the end of the month. (Associated Press)

Commentary, Analysis, and Art

At The Digital Circuit, Scott Simmie looks at how hackers are selling kits to disable the geofencing in drones made by DJI.

At the Hill, Paul Scharre argues that the U.S. should start treating drone exports the same way it treats exports of manned aircraft.

At Popular Mechanics, David Hambling looks at the technology underpinning a U.S. drone designed for research missions in the Arctic.

At War on the Rocks, Ben Brewster argues that the U.S. Marine Corps needs a long-endurance surveillance and strike drone like the Reaper or Gray Eagle.

In a speech in Washington, Gen. Mike Holmes argued that the U.S. Air Force needs greater authority to protect its facilities and aircraft against drones. (FlightGlobal)

London’s Gatwick Airport released a video showing how a drone can interrupt air traffic around an airport. (Motherboard)

At Truthout, Alex Edney-Browne looks at how on-the-ground research can shed more light on the effects of U.S. drone strikes.

At Vertical Magazine, Oliver Johnson looks at how a Canadian company is using drones to help fight wildfires.

At CBC, Dean Beeby writes that Transport Canada’s Arctic drone program was delayed because of international arms control regulations.

At Popular Science, Kelsey D. Atherton looks at how Amazon’s drone hub concepts pose big challenges for urban planners.

A drone video captured the extent of the destruction of Mosul, Iraq. (Associated Press)

Know Your Drone

A team of universities, research institutes, and broadcasters is looking to develop swarms of three to five video drones that can be used to film large sporting events. (Horizon)

Serbia’s Military Technical Institute has unveiled a prototype unmanned ground vehicle that is armed with a machine gun and a grenade launcher. (IHS Jane’s 360)

The Korea Aerospace Research Institute conducted flight trials of its TR-60 tiltrotor drone from a moving ship. (IHS Jane’s 360)

NASA has developed onboard software for drones called Safeguard that forces them to land if they come too close to a no-fly zone. (Wired)

Walmart has announced that it will conduct tests for its delivery drone program at an airport in Upstate New York. (New York Upstate)

Drone maker AirDog unveiled the ADII, a multirotor consumer drone optimized to record sports events and other outdoor activities. (The Drive)

In a test, a team at Johns Hopkins University successfully transported a medical sample under temperature control over 160 miles by drone. (SUAS News)

A consortium of three European countries is looking to develop an unmanned ship for use in the oil and gas sector. (Construction.Ru)

Israeli company Flytrex is seeking to use sophisticated air traffic management software to enable drone deliveries. (The Drive)

A Florida-based company has developed a simulated IED-equipped drone for training soldiers. (C4ISRNET)

CASC conducted a flight test of the new CH-5 Rainbow drone at an airport in northeast China. (East Pendulum)

Drones at Work

Drone maker Flyability announced that its collision-resistant Elios drone has been used to inspect the interior of a nuclear reactor building. (Press Release)

The Australian Transport Safety Bureau is investigating a possible collision between a drone and a light aircraft near Adelaide. Nobody was injured in the incident. (ABC) For more on Close Encounters, click here.

Meanwhile, the U.S. Air Force is looking to obtain authority to shoot down small drones over its facilities after a recent close encounter between a F-22 Raptor jet and a drone. (Aviation Week)

Researchers in Boulder, Colorado used drones to survey damage caused to local trees by invasive green jewel beetles. (Daily Camera)

South Korea is looking to deploy a new system to detect North Korean surveillance drones that fly into its territory. (UPI)

A Drone Racing League RacerX quadcopter drone set a new record for the fastest civilian drone, hitting a top speed of 179.3 mph. (CNET)

Researchers at Northwestern University are developing small ground robots equipped with whiskers that allow them to precisely detect their surroundings. (Wired)

Police in Devon, Cornwall, and Dorset in England are launching the country’s first police unit dedicated to using drones. (AP)

Singapore’s upcoming National Day Parade will feature a light show of 300 drones. (The Straits Times)

Police in DeSoto County, Mississippi used a drone to help investigators search for debris from a recent military plane crash in the area. (Fox13)

North Dakota authorities dismissed criminal charges against a man who was accused of using a drone to stalk a group of private security workers at the Dakota Access Pipeline protests last year. (Bismarck Tribune)

The British Army will no longer use the Black Hornet, a micro drone made by Norway’s Prox Dynamics. (IHS Jane’s Defense Weekly)

Industry Intel

The U.S. Office of Naval Research awarded Embry-Riddle University a $900,000 grant to develop advanced communication systems for unmanned surface vehicles. (Press Release)

The National Science Foundation awarded Bakman Technologies a grant to develop a sensor for a drone to monitor emissions that contribute to global warming. (Drone Life)

Colorado’s El Paso County awarded Sanborn Map Company a multi-year contract to provide drones for a variety of missions, including disaster response and construction site monitoring. (Press Release)

The U.S. Coast Guard awarded Riptide Autonomous Solutions a $69,374 contract for an unmanned underwater vehicle. (FBO)

The French Navy awarded ECA Group a contract for unmanned undersea vehicles for mine detection and disposal. (Press Release)  

Germany’s Bundeswehr awarded EMT a $71 million contract for three LUNA NG systems. (IHS Jane’s Defense Weekly)

Thales is reportedly marketing the Watchkeeper surveillance drone to the Indonesian Air Force. (IHS Jane’s Defense Weekly)

The U.S. Department of Defense awarded Autonomous Solutions a contract to apply machine learning and artificial intelligence to autonomous vehicles operating in challenging environments. (Press Release)

CybAero Ab, a Swedish company that makes rotary drones, signed a debt-refinancing deal with Bracknor, a Dubai-based investment firm. (DefenseNews)

For updates, news, and commentary, follow us on Twitter.

I’ve written a few times that perhaps the biggest unsolved problem in robocars is how to know we have made them safe enough. While most people think of that in terms of government certification, the truth is that the teams building the cars are very focused on this, and know more about it than any regulator, but they still don’t know enough. The challenge is going to be convincing your board of directors that the car is safe enough to release, for if it is not, it could ruin the company that releases it, at least if it’s a big company with a reputation.

We don’t even have a good definition of what “safe enough” is though most people are roughly taking that as “a safety record superior to the average human.” Some think it should be much more, few think it should be less. Tesla, now with the backing of the NTSB, has noted that their autopilot system — combined with a mix of mostly attentive but some inattentive humans, may have a record superior to the average human, for example, even though with the inattentive humans it is worse.

Last week I attended a conference in Stuttgart devoted to robocar safety testing, part of a larger auto show including an auto testing show. It was interesting to see the main auto testing show — scores of expensive and specialized machines and tools that subject cars to wear and tear, slamming doors thousands of times, baking the surfaces, rattling and vibrating everything. And testing the electronics, too.

In Europe, the focus of testing is very strongly on making sure you are compliant with standards and regulations. That’s true in the USA but not quite as much. It was in Europe some time ago that I learned the word “homologation” which names this process.

There is a lot to be learned from the previous regimes of testing. They have built a lot of tools and learned techniques. But robocars are different beasts, and will fail in different ways. They will definitely not fail the way human drivers do, where usually small things are always going wrong, and an accident happens when 2 or 3 things go wrong at once. The conference included a lot of people working on simulation, which I have been promoting for many years. The one good thing in the NHTSA regulations — the open public database of all incidents — may vanish in the new rules, and it would have made for a great simulator. The companies making the simulators (and the academic world) would have put every incident into a shared simulator so every new car could test itself in every known problem situation.

Still, we will see lots of simulators full of scenarios, and also ways to parameterize them. That means that instead of just testing how a car behaves if somebody cuts it off, you test what it does if it gets cut off with a gap of 1cm, or 10cm, or 1m, or 2m, and by different types of vehicles, and by two at once etc. etc. etc. The nice thing about computers is you can test just about every variation you can think of, and test it in every road situation and every type of weather, at least if your simulator is good enough,

Yoav Hollander, who I met when he came as a student to the program at Singularity U, wrote a report on the approaches to testing he saw at the conference that contains useful insights, particularly on this question of new and old thinking, and what regulations drive vs. liability and fear of the public. He puts it well — traditional and certification oriented testing has a focus on assuring you don’t have “expected bugs” but is poor at finding unexpected ones. Other testing is about finding unexpected bugs. Expected bugs are of the “we’ve seen this sort of thing before, we want to be sure you don’t suffer from it” kind. Unexpected bugs are “something goes wrong that we didn’t know to look for.”

Avoiding old thinking

I believe that we are far from done on the robocar safety question. I think there are startups who have not yet been founded who, in the future, will come up with new techniques both for promoting safety and testing it that nobody has yet thought of. As such, I strongly advise against thinking that we know very much about how to do it yet.

A classic example of things going wrong is the movement towards “explainable AI.” Here, people are concerned that we don’t really know how “black box” neural network tools make the decisions they do. Car regulations in Europe are moving towards banning software that can’t be explained in cars. In the USA, the draft NHTSA regulations also suggest the same thing, though not as strongly.

We may find ourselves in a situation where we take to systems for robocars, one explainable and the other not. We put them through the best testing we can, both in simulator and most importantly in the real world. We find the explainable system has a “safety incident” every 100,000 miles, and the unexplainable system has an incident every 150,000 miles. To me it seems obvious that it would be insane to make a law that demands the former system which, when deployed, will hurt more people. We’ll know why it hurt them. We might be better at fixing the problems, but we also might not — with the unexplainable system we’ll be able to make sure that particular error does not happen again, but we won’t be sure that others very close it it are eliminated.

Testing in sim is a challenge here. In theory, every car should get no errors in sim, because any error found in sim will be fixed or judged as not really an error or so rare as to be unworthy of fixing. Even trained machine learning systems will be retrained until they get no errors in sim. The only way to do this sort of testing in sim will be to have teams generate brand new scenarios in sim that the cars have never seen, and see how they do. We will do this, but it’s hard. Particularly because as the sims get better, there will be fewer and fewer real world situations they don’t contain. At best, the test suite will offer some new highly unusual situations, which may not be the best way to really judge the quality of the cars. In addition, teams will be willing to pay simulator companies well for new and dangerous scenarios in sim for their testing — more than the government agencies will pay for such scenarios. And of course, once a new scenario displays a problem, every customer will fix it and it will become much less valuable. Eventually, as government regulations become more prevalent, homologation companies will charge to test your compliance rate on their test suites, but again, they will need to generate a new suite every time since everybody will want the data to fix any failure. This is not like emissions testing, where they tell you that you went over the emissions limit, and it’s worth testing the same thing again.

The testing was interesting, but my other main focus was on the connected car and security sessions. More on that to come.

Judging by the frequency that self-driving cars are mentioned in scientific discussions and the media, they are not only the next big thing, but might actually take over as our main means of transportation. Traditional industries like the railways, on the other hand, seem to have lost that race already. But what if new technologies, such as Internet of Things (IoT) devices and Artificial Intelligence (AI), were not only used to create new transportation modes, but to transform old ones as well?

Image: Source: European Environment Agency, 2015

Image: Source: UIC, 2015

A German Heron 1 UAV. Credit: Airbus Defence and Space

May 29, 2017 – June 4, 2017

News

A German court has thrown out a protest filed by U.S. drone maker General Atomics Aeronautical Systems over the German military’s decision to acquire the Israel Aerospace Industries Heron TP drone over the U.S. firm’s Reaper. The decision by the Oberlandesgericht, the country’s high court, allows the Bundeswehr to proceed with the planned acquisition of five Heron TPs, a medium-altitude long-endurance surveillance and reconnaissance drone. (DefenseNews)

Commentary, Analysis, and Art

At War on the Rocks, Jonathan Gillis argues that the U.S. military is not prepared for a future filled with enemy drones.

Also at War on the Rocks, Michael Horowitz considers the ways in which emerging technologies will shape how the U.S. military fights in future conflicts.

In a series of articles at Breaking Defense, Sydney J. Freedberg Jr. looks at how the U.S. military is integrating artificial intelligence into its operations.  

At Defense One, Patrick Tucker writes that Poland is planning to invest in small, lethal drones rather than large unmanned systems like the Reaper.

A study by the University of Washington found delivery drones tend to produce fewer carbon emissions than trucks when traveling short distances. (UW Today)

At TechCrunch, Brian Heater argues that the DJI Spark foldable drone is not quite the “mainstream” drone that it was made out to be.

At Popular Mechanics, Joe Pappalardo considers the role that small, disposable drones will play in the future of warfare.

At ArsTechnica, Sean Gallagher recalls his role in the U.S. Navy’s early experiments with unmanned aircraft.

At the Montreal Gazette, Marc Garneau discusses the potential threat posed by drones to aircraft.

At the Washington Post, Michael Laris considers what is likely to happen in the wake of the federal appeals court’s decision to strike down the FAA’s drone registration rule for hobbyists.

At the Jamestown Foundation, Tobias J. Burgers and Scott N. Romaniuk look at how al-Qaeda learned to adapt to U.S. drone strikes.

The New York Times reports that a former head of the CIA’s drone program will now lead the agency’s Iran operations.

A paper in Remote Sensing offers a survey of the different systems and methods for using drones for marine mammal research. (MDPI)

A paper in Frontiers in Plant Science compares the use of drones and satellite images in monitoring plant invasions.
In Critical Studies in Security, Katharine Hall Kindervater argues that targeted killings are best understood within the context of a shift towards lethal surveillance.

In the Air & Space Power Journal, Lt. Col. Thomas S. Palmer and Dr. John P. Geis II argue that effective counter-drone weapons will be essential in future conflicts.

In the Naval War College Review, Jeffrey E. Kline considers how to effectively integrate robotics into the fleet while recognizing fiscal constraints.

Know Your Drone

Researchers at the Charles Stark Draper Laboratory and Howard Hughes Medical Institute have created a system that turns live dragonflies into steerable drones. (Gizmodo)

A team at the University of Sherbrooke has developed a solar-powered drone than can autonomously land on lakes to recharge its batteries. (IEEE Spectrum)

U.S. firm Drone Aviation Holding Corp. unveiled an automated winch tethering system for DJI Inspire commercial multirotor drones. (Unmanned Systems Technology)

Amazon has been awarded a patent for a shipping label that doubles as a parachute for items delivered by drone. (GeekWire)

Meanwhile, Walmart has been awarded a patent for a system that uses blockchain technology to keep track of delivery drones. (CoinDesk)

The Office of Naval Research is developing a drone that can detect buried mines for use in amphibious landings. (Shephard Media)

Apple announced that its education programming App, Swift Playgrounds, will soon support code-writing for robots and drones. (The Verge)  

Belorussian firms presented a range of new military unmanned aircraft at the MILEX 2017 exhibition in Minsk, including the Belar YS-EX, a medium-altitude long-endurance system. (IHS Jane’s 360)

In a test flight, China’s Caihong solar-powered ultra long-endurance drone reached an altitude of 65,000 feet. (The Sun)

Defense firm Lockheed Martin successfully completed a beyond line of sight pipeline inspection operation with its Indago 2 commercial multirotor drone. (Unmanned Aerial Online)

Robot maker SMP Robotics unveiled the S5 Security Robot, an unmanned ground vehicle. (Unmanned Systems Technology)

In a test, the U.S. Army used two Raytheon Stinger anti-aircraft missiles to intercept two drones. (Press Release)

The U.S. Special Operations Command has completed testing for its Joint Threat Warning System sensor for the Puma hand-launched tactical drone. (Shephard Media)

Aerospace firm Russian Helicopters is developing a fixed-wing vertical take-off and landing drone. (Shephard Media)

The U.S. Army is planning to test its autonomous trucks on a public highway in Michigan later this month. (Voice of America)

Texas Instruments has designed two circuit-based subsystems that it claims could increase the efficiency of battery-powered drones. (Drone Life)

Drones at Work

In a proof of concept demonstration, Drone Dispatch delivered a box of donuts to a customer by drone in Colorado. (CNET)

The organizers of the Torbay Airshow in the U.K. banned the use of drones at the event. (Devon Live)

Police in Snellville, Georgia are investigating various reports of a drone being used to spy on residents in their homes. (WSBTV)

Officers from the Stafford County Sheriff’s Office in Virginia used a drone to find an armed suspect. (WTOP)

The Albany County Sheriff’s Office in New York has acquired a drone for a range of operations. (Albany Times Union)

North Dakota’s governor has established a task force to support the development of counter-drone technologies. (Press Release)

The Israel Defense Forces is equipping infantry, border defense, and combat intelligence corps units with DJI drones. (Times of Israel)

A Russian bank plans to begin using drones to deliver cash to customers. (Forbes)

Industry Intel

Speaking at the Code Conference, Intel CEO Brian Krzanich said that Intel will not develop a consumer drone. (Recode)

Snap, the social media company that owns Snapchat, has acquired Ctrl Me Robotics, a California-based drone startup. (Buzzfeed)

The Australian Ministry of Defense announced that it will invest $75 million in small unmanned aircraft systems, including the AeroVironment Wasp AE, for the Australian Army. (Press Release)

The Netherlands Ministry of Defence selected the Insitu Integrator to replace the Insitu ScanEagle. (Unmanned Systems Technology)

The U.S. Army awarded Six3 Advanced Systems a $10.5 million contract to design and develop a prototype for a squad of human and unmanned assets. (DoD)

Three German firms, ESG Elektroniksystem und Logistik, Diehl Defence and Rohde & Schwarz, have partnered to market the Guardion counter-drone solution. (Shephard Media)

2G Robotics will provide the laser scanning, imaging, and illumination systems for the Norwegian Navy’s Kongsberg Maritime Hugin autonomous underwater vehicles. (Shephard Media)

France’s Direction Générale de l’Armement will take delivery of the Thales Spy’Ranger mini drone beginning in late 2018. (IHS Jane’s Defence Weekly)

For updates, news, and commentary, follow us on Twitter. The Weekly Drone Roundup is a newsletter from the Center for the Study of the Drone. It covers news, commentary, analysis and technology from the drone world. You can subscribe to the Roundup here.

Latvian drone manufacturer Aerones organized the world’s first drone skydive. Credit: Aerones/YouTube

News

A U.S. Court of Appeals has struck down the Federal Aviation Administration’s drone registration requirement for recreational operators. The federal court ruled that the registration system violates the 2012 FAA Modernization and Reform Act, which does not grant the FAA the authority to regulate hobby aircraft. More than 820,000 people have registered their drones with the FAA since the requirement was implemented in 2015. (Recode)

Commentary, Analysis, and Art

At the Harvard Business Review, Chris Anderson examines the economic potential of drones to transform industries like construction.

At Wired, Rhett Allain studies the physics of a quadcopter in flight.

In a statement, Senator John Hoeven (R-ND) urges the Department of Defense to develop an air traffic management system for drones. (Press Release)

In a speech at the Special Operations Forces Industry Conference, General Raymond Thomas said that armed ISIS drones were the “most daunting problem” of the past year. (DefenseNews)

The U.S. Appropriations Subcommittee on Transportation, Housing and Urban Development held a hearing on drones and self-driving cars.

At the Indianapolis Star, Ryan Martin writes that police departments in Indiana are pushing back against a state law that prohibits police from using drones for surveillance.

At War is Boring, David Axe looks at how the U.S. Air Force is using robotic F-16 fighters to test the teaming of manned and unmanned aircraft in combat.

At The Strategy Bridge, Brian M. Michelson considers the challenge of accountability in autonomous weapons.

At the Intercept, Shuaib Almosawa and Murtaza Hussain write that family members of individuals killed in a U.S. drone strike are disputing claims that the men were members of al-Qaeda.

At Vox, Timothy B. Lee writes that artificial intelligence is “getting more powerful, and it’s about to be everywhere.”

At Popular Science, Kelsey D. Atherton looks at how ISIS is developing remote-controlled weapons that appear similar to some of the earliest drones.

At Ars Technica, Megan Geuss visits a drone racing event to discover the appeal that draws would-be racers to the budding sport.

The Digital Forensic Research Lab look at how separatists in Ukraine use drones and text messages to spread propaganda.

Paint By Drone, a graffiti drone system, will create its first two installations in Berlin and Turin later this year. (Progrss)

Know Your Drone

Amazon announced that is has started development of an air traffic management system for its delivery drones. (Bloomberg)

Researchers from MIT’s Computer Science and Artificial Intelligence Laboratory and ETH Zurich in Switzerland are developing systems that enable drones to maintain the exact framing of a scene specified by the operator. (Engadget)

The U.S. Naval Research Laboratory is working to develop solar-powered unmanned aircraft that can remain aloft for extended periods. (R&D Magazine)

Maritime firms Yara and Kongsberg are partnering to develop an autonomous electric cargo ship that produces zero emissions. (Unmanned Systems Technology)

An official at the U.S. Army’s Tank Automotive Research, Development and Engineering Center has said that the service’s next tank will have the ability to operate aerial drones. (War is Boring)

In a test, a robotic co-pilot system developed by Aurora Flight Sciences successfully landed a simulated Boeing 737 commercial airliner. (Aviation Week)  

Researchers at the Georgia Institute of Technology are developing drone swarms in which the aircraft are protected by a virtual bumper area that prevents them from crashing into each other. (Engadget)

The Air Force Research Laboratory released a rendering of what appears to be its planned Low Cost Attritable Aircraft Technology drone. (The Drive)

Meanwhile, the Air Force Research Laboratory presented a number of unmanned aircraft projects at the second biennial Department of Defense Lab Day, including the Ninja counter-drone system and the Low Cost Attritable Aircraft Technology Program. (Press Release)

U.S. firm Endeavor Robotics unveiled a variant of its 710 Kobra ground robot armed with a 7.62mm machine gun. (Shephard Media)

The Unmanned Mine Counter Measure Integrated System, an unmanned undersea vessel built by Russian shipyard SNSZ, has been declared fully operational with the Kazakh Navy. (Press Release)

Singapore-based firm Zycraft announced that its Independent USV completed a test in which it was deployed in the South China Sea for a continuous period of 22 days. (IHS Jane’s 360)

The U.S. Air Force Research Laboratory is developing small unmanned aircraft that can be launched from AC-130 gunships or similar manned aircraft. (IHS Jane’s 360)

During a trial operation off the coast of San Clemente Island, a U.S. Navy MQ-8B Fire Scout  drone helicopter served as a laser designation platform for a Hellfire missile fired from an MH-60S Knighthawk helicopter. (Press Release)

Drones at Work

Japanese fighter jets were scrambled in response to a drone operated by a Chinese vessel over disputed waters in the East China Sea. (Nikkei Asian Review)

A Jordanian Air Force F-16 fighter jet shot down a drone that was flying near the Syrian border.  (IHS Jane’s 360)

Police in South Pasadena, California used a drone to aid in the search for a missing boy. (The Los Angeles Times)  

Officials in Elk City, Oklahoma enlisted students from Embry-Riddle Aeronautical University to survey damage from a recent tornado with a drone. (News9)

Two aerial inspection services companies, AirShark and Unmanned Experts, used drones to inspect a crucial railroad bridge in New York State. (Unmanned Aerial Online)

The West Australia Police air wing is planning to test drones for a range of operations including investigations and search and rescue missions. (The West Australian)

Researchers using drones to study narwhals found that the animals appear to use use their long, sharp tusks to stun their prey. (New Atlas)

U.S. startup DroneSeed has obtained FAA approval to operate multiple drones carrying agricultural payloads. (Unmanned Aerial Online)

Police in Brick Township, New Jersey have purchased a drone for search and rescue and scene documentation. (App.com)

As part of an inauguration ceremony for an unmanned aircraft runway, Virginia governor Terry McAuliffe flew in a remotely piloted airplane. (Press Release)

Researchers at the University of California are using drones to study tortoise habitats in the Mojave Desert. (IGIS)

The Les Nicolles prison in the the U.K. has installed a Sky Fence counter-drone system. (The Telegraph)

The Israeli Air Force is planning to replace its Sea Scan manned maritime patrol aircraft with the IAI Heron 1, a medium-altitude long-endurance drone. (UPI)  

Industry Intel

DroneWERX, a new initiative by the U.S. Special Operations Command and Strategic Capabilities Office, will focus on rapidly acquiring and fielding new drones and robots, swarms, and machine learning and artificial intelligence technologies for special operations. (DefenseNews)

The U.S. Special Operations Command has placed an urgent order for 325 AeroVironment Switchblade loitering munition drones. (Defense One) For more on loitering munitions, click here.

The U.S. Air Force awarded General Atomics Aeronautical Systems a $400 million contract for 36 MQ-9 Reaper aircraft. (DoD)

The U.S. Navy awarded Northrop Grumman Systems a $303.9 million contract modification for three Lot 2 MQ-4C Triton unmanned aircraft and associated equipment. (DoD)

The U.S. Navy awarded Leidos a $299,570 contract for the Open Ocean Counter Unmanned Underwater Vehicle. (FBO)

The Defense Innovation Unit Experimental awarded FlyMotion a $35,388 contract for DJI drones. (FBO)

Delphi will collaborate with BMW, Intel, and Mobileye to develop and field automated vehicles by 2021. (Associated Press)

Silverstone, the British racing circuit, has reportedly contracted Drone Defence to provide counter-drone systems for the Formula 1 race in July. (The Sun)

The University of Aarhus in Denmark awarded YellowScan a $114,316 contract for a UAS LiDAR solution for surveying. (Ted)

Saudi Arabia launched the Saudi Arabian Military Industries, a state-owned military industrial company that will manufacture drones, as well as a variety of other military systems and equipment. (Reuters)

Amazon will open a research center outside of Paris that will focus on developing its Prime Air drone delivery concept. (Venture Beat)

For updates, news, and commentary, follow us on Twitter. The Weekly Drone Roundup is a newsletter from the Center for the Study of the Drone. It covers news, commentary, analysis and technology from the drone world. You can subscribe to the Roundup here.

The Bonirob agribot uses video- and laser-based positioning as well as satellite navigation to find its way around the fields and with cameras and computer-based image analysis, it recognizes and classifies plants (Bosch Deepfield Robotics).

This article was originally published on IEC e-Tech. Click here to view the original post.

Many advances in electric self‑driving car technology and robotics are transferring across to industrial and commercial vehicles, which account for some 60% of the value of the overall electric vehicle market.

In agriculture, the widening use over the next decade of autonomous hybrid or fully electric tractors, robotic machinery and drones could increase farm efficiency and revolutionize how food is produced.

Although some of the technology in farming robots is similar to that of autonomous vehicles, it differs in that operations such as planting seeds, picking vegetables or fruits and localized application of pesticides have individual sensing, manipulation and processing requirements.

Factors promoting the take‑up of agricultural robotics include the promise of increased productivity and efficiency, falling costs of self‑driving technology, reduced availability and rising costs of farm labour and the need to produce more food for a growing global population while crop yields fall in many regions as a result of climate change.

Tractors in transition to electric propulsion

Self‑driving kits, allowing tractors with GPS assistance to follow pre‑programmed routes on large farms, became available some 20 years ago. Nowadays most high‑end tractors are equipped with driverless technology, which is also compatible with combine harvesters. Using GPS, operators can guide tractors and combines to within 30 cm of any plotted location, resulting in more rows in fields and increasing productivity per acre/hectare. More than 300 000 tractors equipped with auto‑steer or tractor guidance were sold in 2016, according to market research company IDTechEx.

Leading European and US agricultural machinery companies have launched prototypes of fully autonomous cabless and driverless tractors fitted with GPS‑guided steering and sensors including radar, laser and Light Imaging, Detection and Ranging (Lidar). The raw sensor data can be used to create an accurate terrain map of both indoor and outdoor environments, while onboard video cameras enhance safety by detecting and avoiding stationary or moving obstacles. Autonomous tractors can also work with other manned machinery.

The standardization work of numerous IEC Technical Committee (TCs) and Subcommittees (SCs) contributes significantly to the performance of cameras and sensing technology used in driverless tractors and other autonomous agricultural machinery. International Standards prepared by IEC TC 47: Semiconductor devices, IEC SC 47E: Discrete semiconductor devices, and IEC SC 47F: Microelectromechanical systems, enable manufacturers to build more reliable and efficient sensors and microelectromechanical systems (MEMS). IEC TC 56: Dependability, covers the reliability of electronic components and equipment.

John Deere has unveiled its new project, the first fully-electric tractor SESAM, or Sustainable Energy Supply for Agricultural Machinery, at the Paris International Agribusiness Show in early 2017 (Photo: John Deere).

The technology for driverless agricultural machinery will allow 24‑hour autonomous operations such as seeding, planting and tillage to take place. It can enable farmers to address concerns about shortages of agricultural labour, while also increasing productivity and efficiency. IDTechEx notes that delays in the large‑scale market introduction of unmanned autonomous tractors are attributable primarily to regulation, high sensor costs and a lack of trust on the part of farmers, not too technical issues.

Tractors are also making the transition to electric propulsion. A prototype fully‑electric tractor unveiled by a leading US manufacturer earlier this year is equipped with two independent 150 kW electric motors for a total power output of up to 300 kW (402 hp). It is powered by a 130 kWh battery pack and can run for four hours on a three-hour charge.

In the transitional stage to fully‑electric tractors, kits are available to transform diesel‑engine machines into diesel‑electric tractors fitted with generators. In addition, a drivetrain that replaces the transmission, differential and axles with four electric wheel motors provides precise control of the drive tyres.

The range of commercially-available electrically‑powered agricultural vehicles extends beyond tractors to self‑propelled feed mixers and wheeled loaders, all with zero emissions, minimal noise and smooth driving characteristics.

Several IEC TCs and SCs draw up International Standards for the electronic systems, sensors, motors and batteries used in the driverless technology found in electric‑powered autonomous vehicles.

IEC TC 69: Electric road vehicles and electric industrial trucks, prepares Standards for motors and motor controllers, onboard electrical energy storage systems, power supplies and chargers.

Kramer launched the first all-wheel-steered fully electric wheel loader in January 2017 (Photo: Kramer).

Since energy for many smaller agricultural robotic vehicles is often supplied by batteries, TC 69 liaises closely with IEC TC 21: Secondary cells and batteries, and its SCs, which prepare International Standards for all secondary cells and batteries. They cover the safety installation principles, performance, dimensions and labelling of the batteries used in electric vehicles. These batteries can be of a number of different technology types including lead-acid, lithium-ion, nickel metal hydride and lithium iron phosphate.

Although electric tractors require far more power than electric cars, by the time they come into commercial production – in about five years – the size, lasting power and cost of tractor batteries should all have improved.

Diesel‑electric hybrid and battery‑electric tractors could be available on British farms as early as 2020, according to a February 2017 report by the UK National Farmers’ Union. The report envisages that, in the near future, autonomous and traditional machines will be used in partnership with one another, and electric agricultural vehicles – some autonomous, some conventional – will be charged using solar power as well as from mains connections.

Small agribots enable precision farming

While large tractors are efficient on larger farms, small electric‑powered mobile robots offer better opportunities for improving productivity on small and medium‑sized farms, says Professor Simon Blackmore, Director of the National Centre for Precision Farming (NCPF) and Head of Engineering at Harper Adams University in the UK. “In 20 years, robotics will have revolutionized agriculture”, he predicts.

Source: vinbot.eu

Automatic and robotic vehicles and mobile devices are already used for seeding, planting and tillage, picking and harvesting, weeding, sorting and packaging and even for pruning vines. A few strawberry harvesters are being trialled commercially, while robotic harvesting of apples is in the late stages of prototyping.

These lightweight agricultural robots (agribots) are capable of working day and night and in poor weather. They can also collect and transmit real-time data on the state of fields and crops, find diseases or parasites and spray pesticides.

Typically, agribots are based on some form of robotic tractor implement platform, wheeled or belt‑driven, and many are powered by electric batteries, motors and drivetrains.

Depending on the robot’s function, on‑board sensors may include biological (including chemical and gas analyzers), water, meteorological, soil respiration or moisture, photosynthesis or Leaf Area Index (LAI) sensors, as well as weed detectors, dendrometers and hygrometers. Other components range from cameras and wireless communications to robotic arms, lights for night‑time operation and solar panels to recharge batteries.

The rise in the use of robotics, together with the growth of precision agriculture, means that many farming practices will change radically. In precision agriculture, “farm data maps together with GPS‑enabled equipment have enabled variable‑rate farming technology, allowing farmers to vary the rate of input application based on the needs of specific sites/patches as opposed to the entire farm”, according to a 2016 report by IDTechEx.

For example, sensors can detect weeds and other forms of stress, enabling a robot to spray only the area affected by the parasite rather than the entire crop.

Before the end of 2017, a Japanese company in Kyoto prefecture plans to open what it describes as the world’s first farm run almost entirely by robots, producing 30 000 heads of lettuce a day. Robots will be involved in every stage of growth from delivering lettuce seedlings, trimming and watering to harvesting and delivering the fully grown produce to the packaging line. The company estimates that using robots will reduce its running costs by around 30%.

In the future, smaller tractors and robots could work together in “swarms” through a cloud‑based approach and provide multiple services, ranging from weeding, planting and applying fertilizer to harvesting and packaging food.

The Mobile Agricultural Robot Swarms (MARS) project, sponsored by the European Union (EU), is developing swarms of small, autonomous robots that can seed fields on their own. The robots are battery‑powered with electric drive mechanisms and are controlled through cloud-based digital technology. The exact placement of each individual seed can be documented and saved in the cloud, with the data used later to carry out cultivation or herbicide application with great precision.

The use of small, mobile agribots also helps to reduce the heavy soil compaction and high energy consumption usually associated with heavy machinery.

IEC standards support multi-billion dollar industry

IDTechEx reported in September 2016 that agricultural robotics already represent a USD 3 billion industry, which will grow to USD 12 billion in 2026. “Tractor‑pulled robotic implements and autonomous robotic de‑weeders will play a substantial part in that growth”, the report adds.

Earlier this year, the Dublin‑based firm Research and Markets predicted there would be even bigger sales of agricultural robots over the next decade, saying that the global market would grow at a Compound Annual Growth Rate (CAGR) of around 11,9% over the next decade to reach approximately USD 28,6 billion by 2025.

IEC standardization work from many IEC TCs and SCs supports this fast‑growing multi-billion dollar industry, with Europe, North America, Australia and New Zealand among the biggest adopters of these technologies.

In a time of “America First,” the benefits of space travel are clouded by the smoke of hyperbole. In reality, there has been over 2,000 inventions courtesy of NASA that are making our lives better here on Earth. Every day, we benefit as much from the journey as from the destination. These innovations include new medicines developed in zero gravity; faster autonomous transportation technologies; and groundbreaking advances in computing (launched above the clouds). The map below illustrates the number of commercial endeavors that have spun out of the nation’s space program since 1976:

NASA has been an incubator of technology since its inception in 1959. This year, NASA unveiled a new web page illustrating its reach into the design of new smart cities and IoT connected homes, called NASA City. This addition to the already extensive NASA site comes on the heels of President Trump’s proposed budget cut of NASA’s funding that would end earth-centric education and innovations, including protecting the planet from an apocalyptic asteroid.  

According to the President’s outline, “the budget increases cooperation with industry through the use of public-private partnerships, focuses on the nation’s efforts on deep space exploration rather than Earth-centric research, and develops technologies that would achieve U.S. space goals and benefit the economy.”

This past week, I visited the Kennedy Space Center to learn firsthand how our lives have been positively changed by the sacrifices of the brave men and women who risked everything for humanity. As a small testimony to these lives lost in the pursuit of science, I have included below a list from NASA’s website of the top innovations we use every day

Health & Medicine

• LED (Light-Emitting Diodes) Lighting –  The LED technology used in space shuttle plant growth experiments has contributed to the development of medical devices to relive “minor muscle and joint pain, arthritis, stiffness, and muscle spasms, and also promotes muscle relaxation and increases local blood circulation.” In fact, the U.S. Department of Defense uses LEDs now as a “soldier self-care” system to treat minor injuries and pain and to improve endurance in combat.
• Infrared Ear Thermometers – NASA developed this thermometer using “infrared astronomy technology to measure the amount of energy emitted by the eardrum, the same way the temperature of stars and planets are measured.”
• Artificial Limbs – NASA’s space robotic and extravehicular activities have now been applied to create more “functionally dynamic artificial limbs.” Additionally, temper foam was developed by NASA which prevents friction between the skin and the prosthetic.
• Ventricular Assist Device – The ventricular assist device (VAD) functions as a “bridge to heart transplant” by pumping blood throughout the body to keep critically ill patients alive until a donor heart is available. “Weighing less than 4 ounces and measuring 1 by 3 inches, the pump is approximately one-tenth the size of other currently marketed pulsatile VADs, making it ideal for children.

Transportation

• Anti-Icing Systems – NASA scientists developed a thermoelectric deicing system called Thermawing, a DC-powered air conditioner for single-engine aircraft called Thermacool. This allows “pilots to safely fly through ice encounters and provides pilots of single-engine aircraft the heated wing technology usually reserved for larger, jet-powered craft.”
• Highway Safety – The cutting of grooves in concrete to increase traction and prevent injury was first developed for the Space Shuttle to reduce aircraft accidents on wet runways. It was later expanded into highway and pedestrian applications.
• Improved Radial Tires – “Goodyear Tire and Rubber Company developed a fibrous material, five times stronger than steel, for NASA to use in parachute shrouds to soft-land the Vikings on the Martian surface.” Goodyear later added this technology to its new radial tire to increase tread life by over 10,000 miles.
• Chemical Detection – Moisture and pH-sensitive sensors were created to warn NASA of potentially dangerous corrosive conditions in the Space Shuttle before significant structural damage occurred. This new type of sensor was later adapted by the Department of Defense for detecting chemical warfare agents and potential threats, such as toxic industrial compounds and nerve agents.

Public Safety

• Video Enhancing and Analysis Systems – Video Image Stabilization and Registration technology used by NASA in space is now in the hands of FBI agents to analyze video footage.  Aside from law enforcement and security applications, the technology has also been adapted to serve military professionals for reconnaissance, weapons deployment, damage assessment, training, and mission debriefing.
• Land Mine Removal – NASA utilizes its surplus rocket fuel “to produce a flare that can safely destroy land mines,” that is able “to reduce propellant waste without negatively impacting the environment.” The flare uses solid rocket fuel to burn a hole in the mine’s case and burn away the explosive contents before it is safely disarmed.
• Fire-Resistant Reinforcement – “The Apollo heat shield was coated with a material whose purpose was to burn and thus dissipate energy during reentry while charring, to form a protective coating to block heat penetration.” Now the the heat shield coating is being used in fire-retardant paints and aircraft foams for aircraft, including a new “intumescent epoxy material” that expands when exposed to heat.
• Firefighter Gear – Firefighting equipment widely used throughout the United States is based on a NASA development that coupled Agency design expertise with lightweight materials developed for the U.S. Space Program.

Consumer, Home, & Recreation

• Temper Foam – “As the result of a program designed to develop a padding concept to improve crash protection” for the Shuttle and airplane passengers, NASA developed temper foam or “memory foam.” The material is now in most mattresses and pillows.
• Enriched Baby Food – “Commercially available infant formulas now contain a nutritional enrichment ingredient that traces its existence to NASA-sponsored research that explored the potential of algae as a recycling agent for long-duration space travel.” The ingredient can now be found in over 90% of infant formulas sold worldwide.
• Portable Cordless Vacuums – Wireless drills and other appliances were created by Black & Decker for the Apollo and Gemini space missions. “For the Apollo space mission, NASA required a portable, self-contained drill capable of extracting core samples from below the lunar surface.” This invention later led to the development of the Dustbuster.
• Freeze Drying Technology – “In planning for the long-duration Apollo missions, NASA conducted extensive research into space food. One of the techniques developed was freeze drying.” The benefits were amazing as freeze drying food kept 98% of the nutrients but weighing 80% less, which is now used to help help homebound seniors maintain a healthy diet.

Environmental & Agricultural Resources

• Harnessing Solar Energy – Solar energy was first utilized in space, and now “homes across the country are now being outfitted with modern, high-performance, low-cost, single crystal silicon solar power cells that allow them to reduce their traditional energy expenditures and contribute to pollution reduction.”
• Pollution Remediation – “A product using NASA’s microencapsulating technology is available to consumers and industry enabling them to safely and permanently clean petroleum-based pollutants from water.” This technology was recently deployed in the cleanup of catastrophic oil spills such as BP’s Deep Water Horizon and the Exxon Valdez. 
• Water Purification – As part of designing a complex system of devices intended to sustain the astronauts living on the International Space Station and, in the future, those who go on to explore Mars, NASA has been turning wastewater from respiration, sweat, and urine into drinkable water for years. This technology is now available for underdeveloped countries where well water may be heavily contaminated.

Computer Technology

• Better Software – NASA is collaborating with tech companies like Google and InterSense “to solve a variety of challenging technical problems ranging from large-scale data management and massively distributed computing, to human-computer interfaces—with the ultimate goal of making the vast, scattered ocean of data more accessible and usable” both in space and on Earth.
• Structural Analysis – NASA has created thousands of computer programs over the decades to design, test, and analyze stress, vibration, and acoustical properties of a broad assortment of aerospace parts and structures (before prototyping even begins). The NASA Structural Analysis Program is now used to design everything from Cadillacs to roller coasters.
• Refrigerated Internet-Connected Wall Ovens – Everything on the International Space Station is monitored and controlled via the Internet, even the oven named “ConnectIo.” ConnectIo is unique as it enables a “user to simply enter the dinner time, and the oven automatically switches from refrigeration to the cooking cycle,” so the meal is ready when the astronaut (or Earth-bound human) is at the table.

Industrial Productivity

• Powdered Lubricants – NASA developed a solid lubricant coating material originally for its aeropropulsion engines, refrigeration compressors, turbochargers, and hybrid electrical turbogenerators. This technology is now saving industrial companies millions of dollars by improving efficiency, lowering friction, and reducing emissions in widespread industrial equipment.
• Improved Mine Safety – “An ultrasonic bolt elongation monitor developed by a NASA scientist for testing tension and high-pressure loads on bolts” is now used for a plethora of applications from the evaluation of railroad ties to groundwater analysis to radiation dosimetry to medical testing for intracranial pressure.
• Food Safety Systems – “Faced with the problem of how and what to feed an astronaut in a sealed capsule under weightless conditions while planning for human space flight, NASA enlisted the aid of The Pillsbury Company to address two principal concerns: eliminating crumbs of food that might contaminate the spacecraft’s atmosphere and sensitive instruments, and assuring absolute freedom from potentially catastrophic disease-producing bacteria and toxins.” Today HACCP is utilized by the U.S. Food and Drug Administration for the handling of seafood, juice, and dairy products.

NASA’s latest private-sector partnership is expanding into enabling the autonomous mobile future. Last year, the space agency teamed up with automaker Nissan to integrate and test autonomous technologies that have been deployed for over two decades on its Mars rovers in consumer ready cars. The partnership’s goal is to have a fully autonomous car on the road by 2020.

According to Nissan CEO, Carlos Ghosn, “The work of NASA and Nissan—with one directed to space and the other directed to earth—is connected by similar challenges. The partnership will accelerate Nissan’s development of safe, secure and reliable autonomous drive technology that we will progressively introduce to consumers beginning in 2016 up to 2020.”

The two organizations have cooperated on technological development in the past. For instance, Nissan used NASA’s research on neutral body posture in low-gravity conditions to develop more comfortable car seats. But hardware and software for self-driving cars could prove to be some of the most transformative technologies to reach mainstream acceptance in the coming years. Nissan joins Google’s Waymo on the Ames Research Center autonomous testing track.

In addition to the Ames facility, the Kennedy Space Center announced last month that it will convert the “Shuttle Landing Facility runway” to a controlled testing ground of driverless cars, as part of its contribution to the Central Florida Automated Vehicle Partnership. This announcement on the heels of its second showing at the Consumer Electronics Show (CES) in Las Vegas in January. NASA made a point of displaying, in particular, its tech transfer program for autonomous cars and robotics.

Terry Fong, director of the NASA Ames Intelligent Robotics Group said, “NASA’s open-source software, VERVE (Visual Environment for Remote and Virtual Exploration), provides the foundation for human-robot teaming in Nissan’s new ‘Seamless Autonomous Mobility’ (SAM) system and CES is a great venue for showcasing this spin-off technology to the general public. VERVE allows humans to provide assistance to autonomous vehicles in unpredictable and difficult situations when the vehicles cannot solve the problem themselves.”

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If you enjoyed this article about space robotics, you may also want to read:

• Should both the successes and failures of space robots curb the ambition of a manned Mars mission?
• Schiaparelli, are you there? The high risks of space robotics again crash home
• Robohub roundtable: Robotics and space exploration
• Space for the masses as helium balloons and remote control planes reach through the stratosphere

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

Caltrain at Palo Alto, CA. Source: Wikipedia Commons

[Editor’s note: According to a recent article on SFGate, Transportation Secretary Elaine Chao has put the brakes on $647 million for Caltrain to go electric. The delay may kill the project entirely.]

Caltrain is the commuter rail line of the San Francisco peninsula. It’s not particularly good; California is, after all, the land of the car commuter, but a plan is underway to convert it from diesel to electric. This made news at the same time as California Republican house members announced they want to put a stop to both this project and the larger California High-Speed Rail that hopes to open in 2030.

For various reasons, they may be right about the high-speed rail — but stop the electric trains? Electric trains are better than diesel; they are cleaner, faster and quieter. But one number stands out in the plan — to electrify 51 miles of track, and do other related improvements, it is forecast to cost over $1.5 billion dollars. That’s around $30M per mile.

So I started to ask, what other technology could we purchase with $1.5 billion plus a private right-of-way through the most populated areas of silicon valley and the peninsula? Caltrain carries about 60,000 passengers/weekday (30,000 each way.) That’s about $50,000 per rider. In particular, what about a robotic transit line, using self-driving cars, vans and buses?

Paving over the tracks is relatively inexpensive. In fact, if we didn’t have buses, you could get by with fairly meager pavement since no heavy vehicles would travel the line. You could leave the rails intact in the pavement, though that makes the paving job harder. You want pavement because you want stations to become “offline” — vehicles depart the main route when they stop so that express vehicles can pass them by. That’s possible with rail, but in spite of the virtues of rail, there are other reasons to go to tires.

Fortunately, due to the addition of express trains many years ago, some stations already are 4 tracks wide, making it easy to convert stations to an express route with space by the side for vehicles to stop and let passengers on/off. Many other stations have parking lots or other land next to them allowing reasonably easy conversion. A few stations would present some issues.

Making robocars for a dedicated track is easy; we could have built that decades ago. In fact, with their much shorter stopping distance they could be safer than trains on rails. Perhaps we had to wait to today to convince people that one could get the same safety off of rails. Another thing that only arrived recently was the presence of smartphones in the hands of almost all the passengers, and low cost computing to make kiosks for the rest. That’s because the key to a robotic transit line would be coordination on the desires of passengers. A robotic transit line would know just who was going from station A to station J, and attempt to allocate a vehicle just for them. This vehicle would stop only at those two stations, providing a nonstop trip for most passengers. The lack of stops is also more energy efficient, but the real win is that it’s more pleasant and faster. With private ROW, it can easily beat a private car on the highways, especially at rush hour.

Another big energy win is sizing the vehicles to the load. If there are only 8 passengers going from B to K, then a van is the right choice, not a bus. This is particularly true off-peak, where vast amounts of energy are wasted moving big trains with just a few people. Caltrain’s last train to San Francisco never has more than 100 people on it. Smaller vehicles also allow for more frequent service in an efficient manner, and late night service as well. (Most commuter trains shut down well before midnight.) Knowing you can get back is a big factor in whether you take a transit line at night.

An over-done service with a 40 passenger bus every 2 seconds would move 72,000 people (but really 30,000) in one hour in one direction to Caltrain’s 30,000 in a day. So of course we would not build that, and there would only be a few buses, mainly for rush hour. Even a fleet of just 4,000 9 passenger minvans (3 rows of 3) could move around 16,000 per hour (but really 8,000) in each direction. Even if each van was $50,000 each, we’ve spent only $200M of our $1.5B, though they might wear out too fast at that price, so we could bump the price and give them a much longer lifetime.

Energy

These vans and cars could be electric. This could be done entirely with batteries and a very impressive battery swap system, or you could have short sections of track which are electrified — with overhead rails or even third rails. The electric lines would be used to recharge batteries and supercapacitors, and would only be present on parts of the track. Unlike old 3rd rail technology, which requires full grade separation, modern technology could produce rails that are only electrified when an authorized vehicle is in contact. Even so, you would not have electrification at any grade crossing.

Other alternatives would be things like natural gas (which is cheap and much cleaner than liquid fuels, though still emits CO2) because it can be refilled quickly. Or hydrogen fuel cell vehicles could work here — hydrogen can be refilled quickly and can be zero emissions. Regular fossil fuel is also an option for peak times. For example the rush hour buses might make more sense running on CNG or even gasoline. The lack of starts and stops can make this pretty efficient.

Getting off the track

Caltrain’s station in San Francisco is quite far from most of the destinations people want to go to. It’s one of the big reasons people don’t ride it. Vans on tires, however, have the option of keeping going once they get to the station. Employers could sponsor vehicles that arrive at the station and keep driving to their office tower. Vans could also continue to BART or more directly to underground Muni, long before the planned subway is ready. Likewise on the peninsula, vans and buses would travel from stations to corporate HQ. Google, Yahoo, Apple and many other companies already run transit fleets to bring employees in — you can bet that given the option they would gladly have those vans drive the old rail line at express speeds. On day one, they could have a driver who only drives the section back and forth between the station and the corporate office. In the not too distant future, the van or bus would of course drive itself. It’s not even out of the question that one of the passengers in a van, after having taken a special driving test, could drive that last mile, though you may need to assure somebody drives it back.

At-grade crossings

I noted above that capacity would be slightly less than half of full. That’s because Caltrain has a fair number of at-grade crossings in the mid-peninsula. Today, these have railway gates. They would be converted to more normal traffic signals. The robotic vehicles would coordinate their trips to travel in bunches, leaving gaps where the cross-street’s light can be turned green. If any car was detected trying to run the red, the signal could be uploaded to allow all the robotic vans to slow or even brake hard. Unlike trains, they could brake in reasonable amounts of time if somebody stalls on the old track. You would also detect people attempting to drive on the path or walk on it. Today’s cameras and cheap LIDARs can make that affordable.

Over time, there is also the option in some places to build special crossings. Because the vans and cars would all be not very high, much less expensive underpasses could be created under some of the roads for use only by the smaller vehicles. Larger vehicles would still need to bunch themselves together to leave gaps for the cross-traffic. One could also create overpasses rated only for lightweight vehicles at much lower cost, though those would still need to be high enough for trucks to go underneath. In addition, while cars can handle much, much steeper grades than trains, it could get disconcerting to handle too much up and down at 100mph. And yes, in time, they would go 100mph or even faster. And in time, some would even draft one another to both increase capacity and save energy — creating virtual trains where there used to be physical ones.

And then, obsolete

This robotic transit line would be much better than the train. But it would also be obsolete in just a couple of decades! As the rest of the world moves to more robocars, the transit line would switch to being just another path for the robocars. It would be superior, because it would allow only robocars and never have traffic congestion. You would have to pay extra to use it at rush hour, but many vehicles would, and large vehicles would get preference. The stations would largely vanish as all vehicles are able to go door to door. Most of the infrastructure would get re-used after the transit line shuts down.

It might seem crazy to build such a system if it will be obsolete in a short time, but it’s even crazier to spend billions on shoring up 19th century train.

What about the first law?

I’ve often said the first law of robocars is you don’t change the infrastructure. In particular, I am in general against ideas like this which create special roads just for robocars, because it’s essential that we not imagine robocars are only good on special roads. It’s only when huge amounts of money are already earmarked for infrastructure that this makes sense. Now we are well on the way to making general robocars good for ordinary streets. As such, special cars only for the former rail line run less risk of making people believe that robocars are only safe on dedicated paths. In fact, the funded development would almost surely lead to vehicles that work off the path as well, and allow high volume manufacturing of robotic transit vehicles for the future.

Could this actually happen?

I do fear that our urban and transit planners are unlikely to be so forward looking as to abandon a decades old plan for a centuries old technology overnight. But the advantages are huge:

• It should be cheaper
• Many companies could do it, and many would want to, to fund development of other technology
• It would almost surely be technology from the Bay Area, not foreign technology, though vehicle manufacturing would come from outside
• They could also get money for the existing rolling stock and steel in the rails to fund this
• The service level would be vastly better. Wait times of mere minutes. Non-stop service. Higher speeds.
• The energy use would be far lower and greener, especially if electric, CNG or hydrogen vehicles are used

The main downside is risk. This doesn’t exist yet. If you pave the road to retain the rails embedded in them, you would not need to shut down the rail line at first. In fact, you could keep it running as long as there were places that the vans could drive around trains that are slowing or stopping in the stations. Otherwise, you do need to switch one day.

National Grid, the UK grid operator, has several ways of ensuring supply can always meet demand. For shorter gaps in generation, it asks electricity suppliers to run their conventional power stations at below maximum potential output and ramp up as needed.

For longer gaps, it ensures power stations, particularly gas-based ones, are kept on standby. Some stations may only be asked to generate power for between several dozen and a few hundred hours a year. Besides contributing to carbon emissions, operating power plants for such short interventions is expensive.

The question is what to do about this problem. We could build less renewable power and make conventional power “greener” instead by removing the CO₂ and burying it underground. Opinion divides on when these carbon capture technologies can be made commercially viable on a large scale. In the UK, unfortunately two government kickstarter projects have floundered due to concerns about costs and departmental disagreements.

An alternative is to install very big (“grid scale”) batteries capable of storing renewable power to be released when required. This has generated a lot of interest lately. But given the costs of current battery technology, grid-scale storage requires expensive upfront investments.

Solutions on demand

While researchers study these problems, the UK is developing an alternative known as demand-side response. One aspect involves rewarding certain electricity consumers for reducing their usage at short notice. This can range from large industrial customers to smaller consumers using power for heating rooms, cooling, lighting or even refrigeration.

Solar thermal energy system in a modern house.

The other aspect of demand response involves asking customers who own equipment that can store power to help balance surges in demand. For example, the owners of a house equipped with solar panels and corresponding battery storage might reduce repayment costs on the equipment by making the battery units available to the grid. Other equipment in this category includes electric vehicles and hospital/university uninterruptible power supply (UPS) units.

Both types of demand response are happening already. Some industrial power customers and certain other companies such as hotel operators have contracts for reducing power, while National Grid has been attracting much bidder interest for power storage schemes and has some underway in parts of the country. This storage is an alternative to deploying large-scale batteries, and promises to be much more economical if we can make it work on a large enough scale.

Once a pool of customers is set up, some devices might not always be available for storage or reducing demand when needed. This needs to be factored into the calculations both to minimise grid disruption and incentivise customers to participate at these times.The problem is that these schemes get more complicated once the pool of customers gets beyond a certain size. Knowing which customers to sign up and what tariffs to offer requires understanding to what extent devices will be available and at what cost, for example.

There can also be undesired effects, such as large simultaneous rebounds in consumption. For example many refrigerators will draw extra power to get their internal temperature below the required level when a demand response period ends.

Finally there’s a potential major security issue: a central system that collects data about energy usage from many devices may be prone to malicious attacks and information tampering. This could undermine both grid balancing and keeping track of what customers are owed.

How AI can help

Emerging artificial intelligence technologies look like providing answers to these challenges. To select the best participants, for example, grid operators will be able to use sophisticated machine-learning techniques to model the behaviour of individual devices and battery storage units by reviewing data from smart meters and sensors.

Smart Grid concept Industrial and smart grid devices in a connected network. Renewable Energy and Smart Grid Technology Smart city design with future technology for living.

Once signed up for grid storage, it should be possible to estimate the useful lifetime of a battery pack or unit by applying prognostic algorithms to its charging/discharging data. Owners will then receive appropriate compensation, plus the added incentive of knowing how long their battery will last.

When it comes to managing devices in the pool, people used to think we could use individual smart meters or control devices to feed a central server in the cloud. But meters are expensive and the short response times require the cloud server to analyse data in milliseconds, which looks unfeasible once many thousands of units are in a pool.

An alternative is to have metering devices which detect demand levels on the grid themselves and reduce power accordingly. These take pressure off the central server and it only requires metering at site level, rather than for every electrical device. But it still leaves you with a complex control problem in coordinating all these individual decisions. We at Heriot-Watt are working on a solution to this using AI-based algorithms.

Another line of AI research draws on insights from algorithmic game theory to develop reward/penalty mechanisms which ensure enough customers in the pool are willing to participate, and actually respond when necessary. Researchers are also optimistic that blockchain protocols, using the same technology as Bitcoin, could underpin a decentralised ledger system that would get round the security risk of having a single storage point for user data.

Numerous AI research groups, both in the UK and elsewhere, have been addressing these challenges, while a number of start-ups have started developing such systems in practice – relatively simple versions of machine learning are now beginning to be used, for instance. The UK has a good chance to be at the forefront of international efforts to make smarter demand response a reality over the next few years.

This article was originally published on The Conversation.

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See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

Credit: Robovalley

By: Jurjen Slump

QR-codes that provide autonomous vessels with traffic information on buoys, ships or port buildings. Algorithms for controlling a ship’s unexpected movements. Fleets of autonomous ships that are monitored from on-shore control centres. Researchers at Delft University of Technology are working on the future of shipping. They envision a naval world that will be drastically different from today’s shipping industry.

The future is unmanned. And while everybody is talking about Tesla and Google’s self-driving cars, one tends to forget about what is happening in the oceans. As of now, robotic ships are only sailing in labs, but they will be eventually steaming out into the real world. Rolls Royce predicts that it will test a fully autonomous, unmanned ocean-going ship by 2035. It won’t be long before remote-controlled ships will appear on the high seas, as is shown in this futuristic video from Rolls Royce.

https://www.youtube.com/watch?v=vg0A9Ve7SxE

Autonomous vessels will have a major impact. “Imagine what will happen if you save cost and time on one of the biggest sectors in the world”, says Vittorio Garofano of the faculty of Mechanical, Maritime and Materials Engineering (3mE) at Delft University of Technology. The benefits are clear: cost reduction, reduced emissions, increased safety and increased cargo capacity, to name a few. Besides, people won’t lose their jobs over this development, as by 2025 a shortage of approximately 150,000 maritime officers is expected.

Credit: Robovalley

Adaptive control algorithms
But there are a lot of challenges that must be met before the captain can leave the bridge and the algorithms take control. For example, which technologies are needed so that autonomous ships can function hundreds of kilometres from shore? How can robotic ships be made as safe as conventional ships? How should they interact with each other and how do you make sure that the power and propulsion systems work properly when nobody’s on board?

These are some of the key challenges that the research of Delft University of Technology focusses on. Several algorithms have been developed to ensure a safe and robust operation, explained PhD student Ali Haseltalab during a colloquium on autonomous vessels last week. “With an adaptive control algorithm, which learns the dynamics of the propeller, you can control the ship perfectly”, Haseltalab told. Other algorithms are developed for power management, fault-detection and health monitoring.

The Grey Seabax
These mathematics are put to the test at a 3mE-laboratory, which consists of two giant water tanks with QR-codes on the sides. To study the dynamical behaviour of autonomous vessels, researchers built 3 prototypes: The Grey Seabax, the Amphibian and the Delfa-1. The Grey Seabax is a remote-controlled vessel or RCV – the first essential step towards a fully autonomous ship.

One of the things Garofano and his colleagues are working on is a robust communication infrastructure. The Grey Seabax recognises QR-codes and will be able to respond accordingly. These binary markers can be used for several purposes: they could represent a waypoint, a traffic redirection signal or a building ashore.

Credit: Robovalley

Distributed control
The computer lies at the heart of robotic ships. To enhance safety, it is important that the central computer hands over as much as control to intelligent sensors and actuators. With the Amphibian and Delfia-1, research is being done on the shift from centralised to distributed control. “If something fails, the system continues”, Garofano says. “That increases the survivability.”

With the Amphibian being a hovercraft, new transportation routes can be explored. But the vessel is still very difficult to control, tells Garofano. “GPS offers an accuracy of metres, but we need millimetres.”

Credit: Robovalley

Surveillance and inland shipping
Back to the future. Where will the first robotic ships be deployed? For surveillance, maritime litter collection, patrolling and inspection, says associate professor Rudy Negenborn. “They can be used for monitoring water quality, to make sure that nobody can dump chemicals into the ocean unnoticed.”

Negenborn thinks that the big container shipping corporations will be the last to switch to robotic ships. They will first appear on the rivers. “For inland shipping businesses, the salary costs are relatively high compared to big container ships”, says Negenborn. “For them, autonomous shipping is more interesting.”

Safety
All researchers agree that, in the end, safety will be one of the biggest advantages of robotic ships. Nowadays, at least 70 percent of all incidents at sea are caused by human error. Autonomous shipping will lead to a drastic reduction of the number of incidents and casualties. “Robots will ensure consistency of operations”, explains Haseltalab. “Autonomous systems will always be there. They don’t get tired.”

If you liked this article, you may also be interested in reading more about robotic ships and underwater drones:

• Designing and deploying a fleet of autonomous boats on the canals of Amsterdam
• Who goes where? Simulated robot boats self-organize to defend against attacks
• Robots Podcast #132: The OpenROV project, with Eric Stackpole and David Lang
• CoCoRo: Tracking the development of the world’s largest autonomous underwater swarm
• Unmanned and underneath: Stay in the know about underwater drones

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

An Immersion Vortex 250 drone collides with the end of the spray from a water cannon, part of the counter-unmanned aerial system solution developed by the team from Robins Air Force Base, Ga., during the 2016 Air Force Research Laboratory Commanders Challenge at the Nevada National Security Site, Las Vegas, NV., Dec. 13, 2016. Teams were given six months to develop a complete counter unmanned aerial system to aid in base defense. Robins’ system is a multi-layered integrated system which uses a radar and camera system for detection and identification. It also uses a hunter killer drone for interception and a water cannon for shooting it out of the sky. (U.S. Air Force photo by Wesley Farnsworth)

December 12, 2016 – December 18, 2016  

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Field Guide to Drones in Syria and Iraq

In Syria and Iraq today, there are more drones, made in more countries and flown by more groups, than in any previous conflict. We have worked through years of records in order to identify every type of drone known to be operating in the conflict. Here is a guide to these systems, who makes them, who operates them, and how they are being used.

News

China seized a U.S. Navy underwater drone in the South China Sea. The Littoral Battlespace Sensing Glider, a small unmanned undersea vehicle designed for long-distance survey missions, was being operated from the USNS Bowditch, an oceanographic survey ship. Following negotiations, Beijing said it would return the drone. (Wall Street Journal) For more on unmanned undersea vehicles, click here.

Amazon conducted its first drone delivery on December 7 in Cambridgeshire, England. The drone delivered an Amazon Fire streaming device and a bag of popcorn. The two-mile delivery took thirteen minutes from order to completion. Amazon announced that it plans to carry out further drone deliveries to customers in the area around its Prime Air testing site. (New York Times)

The United Nations Convention on Certain Conventional Weapons voted to begin formal discussions on lethal autonomous weapons systems in 2017. The vote will establish a group of government experts, the next step towards a potential ban on future autonomous weapons. (TechRepublic)

A Tunisian aviation engineer linked to Hamas was killed in southern Tunisia, allegedly by Israeli Mossad agents. Mohammed Al Zoari reportedly helped build unmanned aircraft for Hamas and Hezbollah. (Haaretz)

Commentary, Analysis, and Art

At the Guardian, Bradley L. Garrett and Adam Fish look at how drones are reshaping ownership of urban airspace.

At CIMSEC, Heiko Borchert reflects on some of the long-term consequences of China’s seizure of the U.S. underwater drone.

At Lawfare, James Kraska and Raul Pedrozo argue that China’s capture of the U.S. drone violates the law of the sea.

Also at Lawfare, Julian Ku argues that the drone incident in the South China Sea exemplifies how “China is veering further away from a putative rules-based global order.”

At the Christian Science Monitor, Peter Ford writes that China’s seizure of the U.S. drone will set the tone for the Trump administration’s relationship with China.

At the Verge, Ben Popper looks at what the U.S. Navy might have been using the underwater drone for before it was captured by China.

At the Miami Herald, Carol Rosenberg writes that defense attorneys for the victims of the USS Cole attack are seeking information from the federal government regarding an individual killed in a U.S. drone strike.

At TechRepublic, Jonathan Chadwick writes that effective human pilots are crucial when it comes to using drones for environmental management.

In a podcast at Drone Radio Show, Colin Snow discusses drone industry trends in 2016 and how videography remains a major vertical for drone businesses.

In an interview with Bloomberg, Cameron Chell argues that there will continue to be growth in 2017 in specialized drone businesses that serve particular industries.

At Wired, Eric Adams writes that the forthcoming General Atomics Protector remotely piloted aircraft will be able to fly in the same airspace as civil aviation in Europe.

At Vocativ, Campbell MacDiarmid looks at how ISIL uses drones to guide suicide bombers to their targets.

In an interview with the U.S. Air Force, Airman 1st Class Matthew recalls his first drone strike.

At Just Security, Rachel Stohl writes that Jameel Jaffer’s The Drone Memos offers a “critique of the shortsighted nature of Obama administration policies” regarding targeted killing.

At Defense One, Marcus Weisgerber looks at how U.S. weapons are increasingly being built by robots.

At C4ISRNet, Mark Pomerleau looks at how the U.S. Navy is seeking to integrate the MQ-25 unmanned refueler into carrier operations.

At War on the Rocks, Benjamin Jensen argues that the new U.S. administration should take a broader view on the third offset strategy beyond adopting new technologies.

At IEEE Spectrum, Toby Walsh argues that the United Nations should ban lethal autonomous weapons systems.

At KCBY, Dan Rascon examines how one teenager’s drone invention landed him a spot on one of Time magazine’s lists of influential people.

The latest edition of Interface Focus journal features 18 articles on how engineers are borrowing tips from nature to design the next generation of drones. (Seeker)

At KQED Science, Craig Miller looks at how heat-seeking drones could help firefighters reduce fire deaths.

At the Motley Fool, Rich Smith writes that the future TERN tailsitter drone could outclass the F/A-18 and F-35.

Know Your Drone

Car maker Ford is developing a system to equip its self-driving cars with drones. (Phys.org)

Researchers at the University of Zurich are developing small drones that can autonomously navigate through tight openings. (Digital Trends)

Researchers at several Japanese universities are developing a construction robot for disaster relief. (Press Release)

The Ohio Controlling Board approved a project to build a ground-based sense and avoid radar to test drones beyond line of sight. (Columbus Business First)

A team from William Carey University College of Osteopathic Medicine are developing a medical drone designed specifically for first responders. (Fox News)

Two Afghan brothers have developed a drone that detects and detonates landmines. (Voice of America)

Researchers at the NASA Jet Propulsion Laboratory are experimenting with underwater drones as a possible option to explore the oceans on Jupiter’s Moon, Europa. (Digital Trends)

Iran’s Army has reportedly unveiled two military drones: the Oghab, a strike drone, and the Shahin, a reconnaissance system. (Press TV)

Meanwhile, Iran unveiled a jammer gun designed to bring down rogue drones. (Popular Science)

U.S startup LiquidPiston is developing a small rotary engine for use on unmanned aircraft. (Aviation Week)

Israeli firm Advanced Programs Group is developing two short take-off and landing military drones. (FlightGlobal)

The U.S. Office of Naval Research released details and video of a recent test of its swarming drone boats. (Engadget)

Canadian drone maker The Sky Guys has unveiled the DX-3, a commercial fixed-wing drone with 24-hour flight endurance. (Unmanned Systems Technology)

An investigation by the National Transportation Safety Board found that a portion of the wing of Facebook’s Aquila, a high-altitude prototype drone, detached from the aircraft during its maiden flight this summer. (The Verge)

Researchers at Imperial College London have developed a drone that can both dive into the water and then launch itself back into the air. (Press Release)

The U.S. Naval Air Systems Command issued a Request for Information for a small surveillance and reconnaissance drone with a long endurance capability. (IHS Jane’s 360)

The U.K. and France signed an agreement for the next phase of development for the U.K.-France Unmanned Combat Air System Demonstrator Programme. (Press Release)

Drones at Work

The Swiss Federal Aviation Office has released an interactive map showing where drone operators can and cannot fly in the country. (The Local)

AirMap will begin issuing digital certificates to its drone users. (PC World)

UNICEF and Malawi’s government are exploring the use of mapping drones to assist humanitarian relief missions. (Reuters)

A North Korean news website is claiming that a defector group is planning to use explosives-equipped drones to destroy statues of the country’s former leaders. (BBC)

Atmospheric scientists are using drones to measure methane levels at the trade wind inversion over in the South Atlantic. (Spectrum IEEE)

The Somerset County Sheriff’s Office in New Jersey has acquired a drone for Alzheimer’s patients who go missing. (NJ 1015)

The Stafford County Sheriff’s Office in Virginia is planning to acquire a drone. (Fredericksburg.com)

Officials in Bangor, Maine used a drone to assist in the search for a missing man. (Bangor Daily News)

The City of Orlando passed an ordinance restricting the use of drones. (WESH 2)

Scientists at Natural Resources Canada are using drones to map coastal erosion in the Western Arctic. (Local Express)

The Cobb County Police Department is looking to buy a drone for car accident investigations. (Marietta Daily Journal)

The San Diego County Sheriff’s Department used its drone for the first time in a standoff in October, reports have revealed. (Voice of San Diego)

A team from Jordan College of Agricultural Sciences and Technology is experimenting with drones to support almond growing operations during droughts. (Mercury News)

Industry Intel

Infosys has invested an undisclosed amount in ideaForge, an Indian startup that aims to use drones for industrial applications. (Economic Times)

The U.S. Navy awarded Metron a $29.8 million contract to advance the development of autonomy in unmanned undersea vehicles. (DoD)

The U.S. Army awarded General Atomics Aeronautical Systems an $80 million contract for the continuation of contractor logistics support for the Gray Eagle system.

A report by Market Forecast predicts that the global military drone market will grow to $13.9 billion by 2016. (Press Release)

For updates, news, and commentary, follow us on Twitter. The Weekly Drone Roundup is a newsletter from the Center for the Study of the Drone. It covers news, commentary, analysis and technology from the drone world. You can subscribe to the Roundup here.

Source: commaai

There have been few postings this month, as I took the time to enjoy a holiday in New Zealand around speaking at the SingularityU New Zealand summit in Christchurch. The night before the summit, we enjoyed a 7.8 earthquake not so far from Christchurch, whose downtown was 2/3 demolished after quakes in 2010 and 2011. On the 11th floor of the hotel it was a disturbing nailbiter of swaying back and forth for over 2 minutes — but of course, swaying is what the building is supposed to do, that means it’s working. The shocks were rolling, not violent, and in fact, we got more violent jolts from aftershocks a week later when we went to Picton.

While driving around that region, we encountered this classic earthquake scene on the road:

There were many like this and in fact the main highway of the South Island was destroyed long-term not too far away, cutting off several towns. A scene like this makes you wonder just what a robocar would do in these situations. I already answered this question in a blog post on how to handle a tsunami. Fortunately, there was only a mild tsunami for this quake. A tsunami will result in a warning in the rich world and the car will know the elevation map of the roads and know how to get to high ground. In some places, like Japan, there is also an advanced earthquake warning system that tells you quakes are coming well before they hit since electrons go much faster than seismic waves. With such a system, robocars should receive a warning and come to a stop unless they need to evacuate a tsunami zone. Without such a warning, we still could imagine the road cracking and collapsing in front of you as might have happened on this road. Of course, the cones and signs that warned me days later would not be present.

The answer again lies in the fact that pictures (like mine) will be used to create situations like this in a simulator and car developers will be able to test their systems with simulated quake damage. I’ve spoken since 2010 on the value of a shared simulator environment and I think if government agencies like NHTSA want to really help development, providing funding and tools for such an environment would be a good step. NHTSA’s proposal that all developers share their logs of all incidents would clearly make such a simulator better, but there is pushback because of the proprietary value of those logs. When it comes to strange situations like earthquakes, I doubt there would be much pushback on having an open and shared simulator environment.

New Zealand’s government is taking a very welcoming approach to robocars. They are not regulating for a while and have invited developers to come and test. They have even said it’s OK to test unmanned vehicles under some fairly simple rules. NZ does not have any auto industry and it’s quite remote, but we’ll see if they can attract developers to come test. Their roads feature something you don’t see much in the USA — tons and tons of one-lane bridges and other one-lane stretches of highway. Turns out that robocars, with a little bit of communication, can make efficient use of one-lane two-way roads, so it might be worth exploring.

[Editor’s note: Christchurch will host New Zealand’s first trial of a fully autonomous electric vehicle next year. The trials will largely be conducted on the Christchurch Airport campus, starting on private roads with no public present, with the long-term aim of moving to public roads once the safety case has been made and all regulatory approvals are in place.]

Open Source Comma One box

Speaking of Open, today Comma.ai, which previously had declared they were giving up on their neural network autopilot due to NHTSA threats today announced they have open sourced their software, along with hardware designs and case designs. NHTSA did not want them making an autopilot and said they could not simply rely on the fact that drivers were told they must be diligent, It will be very interesting to see how NHTSA reacts to the release of open designs that anybody can then install on their car.

The automotive industry has had a long history of valuing the tinkerer. All the big car companies had their beginnings with small tinkerers and inventors. Some even died in the very machines they were inventing. These beginnings have allowed people to do all sorts of playing around in their garages with new car ideas, without government oversight, in spite of the risk to themselves and even others on the road. If a mechanic wants to charge you for working on your car they must be licenced, but you are free to work on it yourself with no licence, and even build experimental cars. You just can’t sell them. And even those rights have been eroded.

Clearly far fewer people will have the inclination to build an autopilot using the comma.ai tools by themselves. But it won’t be that hard to do, and they can make it easier with time, too. One could even imagine a car which already had the necessary hardware so that you only needed to download software to make it happen.

In recent times, there has been a strong effort to prevent people with tinkering with their cars, even in software. One common area of controversy has been around engine tuning. Engine tuning is regulated by the EPA to keep emissions low. Car vendors have to show they have done this — and they can’t program their car to give good emissions only on the test while getting better performance off the test as VW did. But owners have been known to want to make such modifications. Now we will see modifications that affect not just emissions but safety. Car companies don’t want to be responsible if you modify the code in your car and there is an accident involving both their code and yours. As such, they will try to secure their car systems so you can’t change them, and the government may help them or even insist on it. When you add computer security risks to the mix — who can certify the modified car can’t be taken over and used as a weapon? — it will get even more fun.

I will also point out that I suspect that comma’s approach would not know what to do about the collapsed road because it would never have been trained in that situation. It might, however, simply sound an alert and kick out, not being able to find the lane anymore.

Regulatory pushback

Regular readers will have seen my strong critique of the NHTSA rules. The other major news during my break was the pushback from major players in the public comment on the regulations. In some ways, the regulations didn’t do enough to give vendors the certainty they need to make their plans. At the same time they were criticized for not giving enough flexibility to vendors. In addition, as expected, they resist giving up their proprietary data in the proposed forced sharing. I predict continued ambivalence on the regulations. Big players actually like having lots of regulations, because big players know how to deal with that and small players don’t.

This post originally appeared on robocars.com.

By Ethan Bilby.

Field robots and plane-based remote sensors can patrol the earth and the sky to monitor the gases that cause climate change. Standing on three large wheels that help it avoid getting stuck in the soil, the Field Flux robot is able to lower two sampling chambers held on large arms to test soils for tiny amounts of nitrous oxide (N2O).
Though carbon dioxide (CO2) is better known when it comes to climate change, N2O has a global warming potential that’s over 300 times higher. In other words, a single molecule of N2O is as damaging as 300 CO2 molecules.

‘One of the great difficulties in quantifying N2O emissions from agriculture is that it changes with a factor of 100 from one day to the next and one spot to another,’ said Professor Lars Bakken, from the Norwegian University of Life Sciences in Oslo. He is a microbial ecologist on the NORA project, which is working out ways to reduce N2O emissions from soils and developed the monitoring robot alongside Norwegian company Adigo. ‘This is actually the whole reason we made the field robot. If you want to quantify emissions from a field experiment you have to measure over and over and over in many plots,’ said Prof. Bakken.

The Field Flux prototype can measure the amount of the greenhouse gas nitrous oxide in agricultural fields. Image: NORA

Using the robot, a field that took 27 hours to test manually can be done in just one hour. Those measurements are crucial in controlling N2O as they could allow farmers to treat their soils where needed. The N2O is produced by some soil microorganisms during periods when the soil is not well aerated, for example during heavy rain, or when the soil is tightly packed. Those organisms, mostly bacteria, then use nitrogen oxides instead of oxygen for respiration. Several of those bacteria can respire N2O by using a very special enzyme, the N2O reductase. The researchers in the NORA project discovered that this enzyme is prevented from functioning correctly in acidic soils, and also when there isn’t enough copper present.

‘We looked at the biology of these organisms and how they regulate those processes that are responsible for N2O emissions,’ said Professor Åsa Frostegård, also a microbial ecologist at Norwegian University of Life Sciences, and the coordinator of the Marie Skłodowska-Curie Actions-funded project. ‘We see large differences in how different microbes do these things.’

Image: ADIGO

Armed with that knowledge, it could be possible for farmers to reduce N2O pollution by changing the acidity or copper content in their soils. That could mean using so-called mafic rocks, minerals that are rich in iron and magnesium, to neutralise acid in the soil, instead of traditional liming, which can increase CO2.

Gazing at clouds

Monitoring particles once they get into the atmosphere, where they are known as aerosols, isn’t any easier. Researchers in the Marie Skłodowska-Curie Actions-funded ITaRS project, led out of the University of Cologne in Germany, are using remote aircraft-based sensors and ground-based measurements to get a handle on when clouds are likely to form or develop precipitation.

‘One of the major uncertainties in atmospheric models is how clouds interact with aerosols in the atmosphere. We don’t even know in detail how clouds are formed,’ said Dr Maria Barrera Verdejo, an ITaRs fellow working with lidars and microwave radiometers. To form, clouds need particles such as dust or pollen for water to condense around. Improving the precision of ground- and air-based measurements provides researchers with new data they can use to better understand atmospheric phenomena, for example how and under which conditions storms will develop. ‘My measurements can be used for something that is called data assimilation in weather forecasting. You feed in what the atmospheric state is, and the model calculates what is going to happen next,’ Dr Barrera said.

With the measurements deployed within the ITaRS project, researchers were able to answer some scientific questions related to the understanding of atmospheric events. For example, information about what humidity, pressure conditions and particle concentration are required for a cloud to start drizzling, was obtained thanks to passive microwave sensors combined with radar measurements.

That data provided by ITaRS not only improves our knowledge on the atmospheric behaviour, but also helps to reduce uncertainties on climate models, which translates to a better understanding of climate change.

This article was originally published by Horizon Magazine.

If you enjoyed this article, you may also want to read:

• Swarms of precision agriculture robots could help put food on the table
• Top 10 technologies in precision agriculture
• Farming with robots
• Protecting European wine: Vinbot rover optimises harvest and quality
• Robots for a sustainable future

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

At Starship, we announced our first pilot projects for robotic delivery which will begin operating this summer. We’ll be working with a London food delivery startup Pronto as well as German parcel company Hermes and the Metro Group of retailers, plus Just Eat restaurant food delivery to trial on-your-schedule delivery of packages, groceries and meals to people’s homes.

(It’s a nice break from Tesla news — and besides, our little robots weigh so little and move so slowly that even if something went horribly wrong and they hit you, injury is quite unlikely.)

Hermes, which does traditional package delivery is very interested in what I think is one of the core values of robot delivery — namely delivery on the recipient’s schedule. Today, delivery is done on the schedule of delivery trucks, and you may or may not be home when it arrives. With a personal delivery robot, it will only come when you’re home, reducing the risk of theft and lost packages. Robots don’t mind waiting for you.

The last mile is a huge part of the logistics world. Starship robots will get you packages with less cost, energy, time, traffic, congestion and emissions than you going to the store to get it yourself. They use a combination of autonomous driving with human control centers able to remotely fix any problems the robots can’t figure out. Robots don’t mind pausing if they have a problem and our robots can stop in under 30cm. As we progress, operation will reach near full autonomy and super low cost.

((More details at the Starship press release. I am on the advisory team at Starship.))

If you enjoyed this article, you may also enjoy reading:

• Robohub Digest 11/15: Service and consumer robots catching on
• Going the last mile with robots
• Calculating why we should make a lot more robocars
• Delivery robots from Starship Technologies
• Self-driving trucks are coming — what will that mean?

Mercedes Benz autonomous concept car at the IAA 2015. Photo: VanderWolf Images/Bigstockphoto

What does that car of the future look like? There is no one answer; in this world, the car that is sent to pick you up can be tailored for your trip. The more people traveling, the bigger the car. If your trip does not involve a highway, it may not be a car capable for the highway.

With Mobility on Demand, you don’t buy a car, you buy rides. That’s certainly Uber’s plan, and is a plan that makes sense for Google, Apple and other no-car companies. But even Daimler, with Car2Go/Car2Come, BMW with DriveNow and GM with Lyft plan to sell you a ride rather than a car because it’s the more lucrative thing to do.

So, what does that car of the future look like? There is no one answer; in this world, the car that is sent to pick you up is tailored for your trip. The more people traveling, the bigger the car. If your trip does not involve a highway, it may not be a car capable for the highway. If your trip is up to a mountain cabin, it’s more like an SUV, but maybe not using an SUV to get a bottle of milk, like we do today. If it’s for a cruise to the beach on a sunny day, the roof may have been removed at the depot. If it’s for an overnight trip to a country home, it might be just beds!

I’ve outlined many of these changes in this article on design changes in cars but today I will focus on the incredibly cheap and simple design of what should become the most common vehicle made, namely the car designed for a short urban trip by one person. That’s 80% of trips and around 45% of miles, so this should be a large fraction of the fleet. I predict a lot of these cars will be made every year — more than all the cars made today, even though they are used as taxis and shared among many passengers.

What does it look like?

Small

Toyota i-Road concept car. Source: Wikipedia Commons

A car for 1-2 people will be small. It will probably be around 1.5m wide, narrow enough that you can fit two in a lane, and have it park efficiently when it needs to wait. If it’s for just one person, it won’t be very long either. For two people, there will be a “face to face” configuration which is longer and a “tandem” configuration, which is a bit shorter. The 2 person vehicles aren’t a lot bigger or heavier than the one person, so they might be the most common cars since you can serve a solo rider fairly efficiently with one, even if not perfectly efficient.

A car that is so narrow cannot corner quickly. A wide stance is much more stable. There are a few solutions to that, including combinations of these:

• The wheels bank independently, allowing the vehicle to lean like a motorcycle when in corners. This is the best solution, but it costs some money.
• Alternately, it’s a two-wheeler, which is also able to lean, but has other tricks like the LIT Motors C-1 to stay upright.
• It’s electric and has all the batteries in the floor, giving it a very low center of gravity. (One extreme example of this is the Tango, which uses lead batteries deliberately to give it that stability.)
• It never goes on fast roads, so it doesn’t need to corner very fast, and its precision robot driving assures it never corners so fast as to becomes unstable and also plans its route accordingly.

Lit C1 Gyroscopically Balanced Electric Motorcycle Source: Flickr/DeBold

Not super aerodynamic

The car already has a big win when it comes to aerodynamic drag by only being half-width. The non-highway version probably gives back a bit of that because you don’t need to worry as much about that if you are not going fast. Energy lost to drag goes up with the square of velocity. So, a 30mph car has 1/4 the drag of a 60mph car, and 1/8th the drag of a similar car of full width. The highway car needs to be shaped as close to a “teardrop” as you can, but the city car can get away with being a bit taller for more comfortable seating and entry/exit.

Most car companies are remaking themselves into tech startups as they move toward offering fully autonomous self-driving vehicles. Yet thousands of tractors already use self-driving kits as do hundreds of tugs, lifts and trucks. Self-driving aftermarket kits are beginning to be offered in multiple markets. What's going on?

Cruise Automation just got acquired by GM for $1 billion. Up until now, Cruise was known as the developer of a $16,000 aftermarket kit to turn select cars into self-driving cars. Does GM want to supplement their parts business with self-driving kits? Or did they spend all that money to acquire talent?

Cruise Automation isn't the only kit developer: Comma.ai promises a $1,000 kit by the end of this year and just got a $3.1 million seed round of funding; Perrone Robotics is already selling a high-end kit for R&D and testing with funding from DARPA and the IIHS. Other companies are listed below. What's going on? Are aftermarket kits really that much in demand? 

Media today seems most focused on suggesting that the industry is quickly moving toward preventing crashes from ever occurring instead of just protecting occupants from crashes even though there are many other reasons for self-driving cars (eg, fuel efficiency, lowering carbon emissions, enabling safe transportion for the elderly, and improving traffic congestion).

Andrew Ng's timetable for self-driving cars

From an interview in Wired of Andrew Ng, Chief Scientist of Baidu; and Chairman and Co-Founder of Coursera.

I think self-driving cars are a little further out than most people think. There’s a debate about which one of two universes we’re in. In the first universe it’s an incremental path to self-driving cars, meaning you have cruise control, adaptive cruise control, then self-driving cars only on the highways, and you keep adding stuff until 20 years from now you have a self-driving car. In universe two you have one organization, maybe Carnegie Mellon or Google, that invents a self-driving car and bam! You have self-driving cars. It wasn’t available Tuesday but it’s on sale on Wednesday.

I’m in universe one. I think there’s a lot of confusion about how easy it is to do self-driving cars. There’s a big difference between being able to drive a thousand miles, versus being able to drive anywhere. And it turns out that machine-learning technology is good at pushing performance from 90 to 99 percent accuracy. But it’s challenging to get to four nines (99.99 percent).

Scramble for talent

As car companies move in the direction of providing self-driving cars, most have proprietary roadmaps and big needs for software and other engineering talent. They have all set up research facilities in Silicon Valley and throughout academia. The Wall Street Journal mapped car company locations in Silicon Valley (shown below) which attests to their proliferation. Not included on this map are the new tech startups profiled in this article.

Self-driving kits and embedded software for cars, buses and trucks

Because the auto industry is so much larger and visible to the consumer public, the remainder of this article will focus on self-driving kits and other software and AI offered to the auto, transportation and trucking industries, as well as to the consumer aftermarket.

Self-driving kits

• Cruise Automation just got acquired by General Motors for what Forbes reported as “north of a billion dollars.” GM has stated their goal of creating the industry’s biggest driverless-vehicle fleet which is why GM paid such a steep purchase price for Cruise, invested $500 million into Lyft, and another $25 million to acquire the employees and technology left over from Sidecar, a ride-sharing service that shut down last December. Certainly these acquisitions are both a talent and a technology grab to help them facilitate their fleet-vehicle goal.
• Comma.ai, a San Francisco startup headed by George Hotz, the hacker that, at age 17, was the first person to unlock an iPhone, and at 21, cracked the encryption schema on the PlayStation3, got $3 million in funding from Andressen Horowitz and others for his plans to produce a self-learning, self-driving kit for under $1,000 and deliver that kit by the end of 2016. Nvidia donated $30K of their new GPUs, which are tailor-made to run deep learning algorithms, to Comma. Nvidia GPUs already run the infotainment systems in Tesla cars.
• Perrone Robotics, a Charlottesville, VA funded by DARPA and the Insurance Institute for Highway Safety (IIHS), has created and patented a general purpose autonomous vehicle operating system to assist researchers and auto engineers in developing and testing their vehicle applications including testing their security to protect against hacking.
• Hi-Tech Robotic Systemz, a Gurgaon, India-based robotics integrator, has branched out into driver assistance systems in the form of aftermarket solutions primarily built onto the embedded ADAS (Advanced Driver Assistance Systems) provided by the car manufacturers.
• ASI (Autonomous Solutions), a Utah-based provider of autonomous driving kits for the mining and farming industries, and testing kits for the automotive and R&D communities, has a whole product line of hardware components that allow users to control vehicles both manually and robotically as well as their Mobius command and control AI and software system. ASI, like Andrew Ng, believes that the charge to fully autonomous self-driving vehicles will likely be a 20-year trickle-down process.
• RobotCar, a project with the UK Department of Transportation and researchers at the University of Oxford, is testing what could be a $150 kit that learns as it goes: “As you drive your RobotCar to work or to the store, the car's systems will be keeping a close eye on the route and, eventually, will know enough to take over for you.”

Embedded software and specialty processors

• Elektrobit is a Finnish supplier of embedded car software for Mercedes, Ford, VW, BMW and Audi, and sold its business to Continental AG last year for $680 million. Elektrobit provides connected car, sensor and autonomous driving systems as well as car company factory automation systems so that the car companies can focus on engineering and building cars.
• Nauto, which just got $12M from Andy Rubin's new incubater Playground, is building automotive networking and safety features for self-driving cars. One particularly valuable technology will be similar to airline black boxes: stored sensor and visual data to help fleet managers and insurance companies detect and understand the cause of accidents and reduce liability claims.
• nuTonomy is developing perception, mapping, localization, and decision-making software for autonomous cars. They are developing algorithms to navigate complex environments, handle parallel, head-in and back-in parking and software that interprets the rules of the road to safely navigate complex itersections.
• Drive.ai, a Silicon Valley AI startup founded by former graduate students out of Stanford University’s Artificial Intelligence Lab, is using deep learning methods to provide solutions for autonomous vehicles from perception to motion planning to controls. Drive.ai just got $12 million in equity funding from undisclosed sources. (Drive.ai is not to be confused with DriveAI, a NJ non-profit working on similar activities and funded by an insurance company.)
• NVIDIA, a long-time provider of graphic processing units (GPUs) to gamers, data centers and the auto market particularly for their infotainment systems, at their recent GPU Tech conference, showed their deep learning self-driving car which boasted 3,000 miles of learning. Nvidia also introduced their new super-computer in a box specially designed to run deep learning programs, the DGX-1. Nvidia donated $30K of these new GPUs, which are tailor-made to run deep learning algorithms, to George Hotz's Comma startup.

Public transport, AGVs and governmental services

• RoboSoft, a French provider of mobility systems to government defense departments and municipal transportation systems. RoboSoft has worked with public transport groups on shuttles, buses and off-public-road shuttles and car fleets and also with warehouse and factory people on AGVs. 
• Zoox is building an autonomous robot taxi fleet and a comprehensive set of systems to support them. “Zoox is developing fully autonomous vehicles and the supporting ecosystem required to bring the technology to market at scale. Zoox aims to provide the next generation of mobility-as-a-service in urban environments.” Zoox joins 11 other companies given permits by California's DMV to test drive autonomous vehicles in California.
• Robot Taxi, a joint venture of Dena and ZMP, is also building an autonomous robot taxi to operate, at least on a test scale, by 2020 in time for the Japanese-hosted Olympics. ZMP's deep learning technology and multi-neural networks will learn about the objects that need to be recognized by their appearance. This technology will then be capable of detecting and recognizing pedestrians, vehicles and other obstacles in real time. Combined with multiple laser sensors the aim is to develop a robust and reliable environment recognition technology that is aware of the vehicle’s situation in ever-changing, real world scenarios.

Key players working on self-driving vehicles

• Google Driverless Car Project, US
• GM-Carnegie Mellong Autonomous Driving Collaborative Research Lab, US
• Uber Advanced Technologies Center, US
• University of Berlin, DE
• Technical University of Braunschweig, DE
• Karlsruhe Institute of Technology, DE
• Bundeswehr University Munich, DE
• VisLab, University of Parma, IT
• Oxford Mobile Robotics Group, UK
• INRIA IMARA, FR
• Navya Technology, FR
• Griffith University, Intelligent Control Systems Lab, AU
• Singapore-MIT-Alliance for Research & Technology, SG
• ETRI, KR

Bottom line

Perhaps the Deere tractor example applies to cars. Deere has had self-driving, autonomous, cab-less concept tractors such as the one shown on the right available for discussion and possible sale but thus far they haven't replaced the self-driving kits which they have been selling for 15 years. Farmers want the air-conditioned and cushioned cabin on their tractors to house all the monitors and other computer and automation technologies for the implements the tractors are towing. They want to remain in charge and the cab has become the hub of computerized farm automation. They say they are waiting for the right time – when fully autonomous tractor systems provide all the services they want and need. And that time is far off in the future.

Maybe car drivers want to remain in charge but are willing to have fun experimenting with low-cost partial self-driving kits or incremental add-on features on new cars until the time – far off in the future – when fully trustworthy autonomous self-driving vehicles take over the transportation marketplace. Maybe the public isn't ready yet to fully trust cars, trucks and buses without drivers. Perhaps self-driving kits are an interim step along the way. 

]]> https://robohub.org/autonomous-truck-platoons-travel-across-europe/ Thu, 14 Apr 2016 15:30:00 +0000 http://robohub.org/autonomous-truck-platoons-travel-across-europe/

A dozen trucks arrived in Rotterdam after traveling across Europe in the European Truck Platooning Challenge. Six different truck makers participated: Scania, Daimler, Volvo, IVECO, MAN and DAF.

Truck platooning involves a convoy of connected trucks that drive and react as a single unit. Acceleration and braking are linked and controlled by computers and WiFi, allowing vehicles to drive much closer together without sacrificing safety while reducing drag and also the cost of drivers and fuel. Each of the six truck manufacturers demonstrated their own platooning technologies.

It is estimated that fuel savings of up to 10% can be achieved with equivalent reductions in CO2 emissions by this type of slipstreaming.

Each of the test vehicles was connected by WiFi, which allowed for the close platooning that wouldn't be possible with human drivers. Trucks used an advanced Wifi-P connection, developed by NXP, and specially designed for automotive applications. The hi-speed WiFi system enables trucks to drive close together and communicate with each other. Everything that the driver in the first truck sees in front of him is projected onto a screen in the second truck.

"The technology is still very much an assistance feature," said Jeremy Carlson, senior analyst for autonomous driving at IHS Automotive. "This type of automated vehicle handles 98 percent of the miles, but you still need to have a human driver ready to take some of the scenarios that come with large trucks, including navigating narrow city roads." 

Truck platooning could happen within the next 10 years and most manufacturers are investing in the technology. Daimler recently announced it was investing more than $500 million into its truck platooning technology, and research reports have forecast that more than 7.7 million truck platooning systems could be on roads around the world by 2025.

Read more

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Platooning. Photo: Dan Boman/Scania

A dozen trucks arrived in Rotterdam after traveling across Europe in the European Truck Platooning Challenge. Six different truck makers participated: Scania, Daimler, Volvo, IVECO, MAN and DAF.

Truck platooning involves a convoy of connected trucks that drive and react as a single unit. Acceleration and braking are linked and controlled by computers and WiFi, allowing vehicles to drive much closer together without sacrificing safety while reducing drag and also the cost of drivers and fuel. Each of the six truck manufacturers demonstrated their own platooning technologies.

It is estimated that fuel savings of up to 10% can be achieved with equivalent reductions in CO2 emissions by this type of slipstreaming.

Each of the test vehicles was connected by WiFi, which allowed for the close platooning that wouldn’t be possible with human drivers. Trucks used an advanced Wifi-P connection, developed by NXP, and specially designed for automotive applications. The hi-speed WiFi system enables trucks to drive close together and communicate with each other. Everything that the driver in the first truck sees in front of him is projected onto a screen in the second truck.

“The technology is still very much an assistance feature,” said Jeremy Carlson, senior analyst for autonomous driving at IHS Automotive. “This type of automated vehicle handles 98 percent of the miles, but you still need to have a human driver ready to take some of the scenarios that come with large trucks, including navigating narrow city roads.”

Truck platooning could happen within the next 10 years and most manufacturers are investing in the technology. Daimler recently announced it was investing more than $500 million into its truck platooning technology, and research reports have forecast that more than 7.7 million truck platooning systems could be on roads around the world by 2025.

]]> https://robohub.org/startup-bringing-driverless-taxi-service-to-singapore/ Sun, 27 Mar 2016 08:27:00 +0000 http://robohub.org/startup-bringing-driverless-taxi-service-to-singapore/

An exciting “driverless race” is underway among tech giants the United States: In recent months, Google, Uber, and Tesla have made headlines for developing self-driving taxis for big cities.

But a comparatively small MIT spinout, nuTonomy, has entered the race somewhat under the radar. The startup is developing a fleet of driverless taxis to serve as a more convenient form of public transit while helping reduce greenhouse gas emissions in the densely populated city-state of Singapore.

“This could make car-sharing something that is almost as convenient as having your own private car, but with the accessibility and cost of public transit,” says nuTonomy co-founder and chief technology officer Emilio Frazzoli, an MIT professor of aeronautical and astronautical engineering.

The startup’s driverless taxis follow optimal paths for picking up and dropping off passengers to reduce traffic congestion. Without the need to pay drivers, they should be cheaper than Uber and taxis. These are also electric cars, manufactured through partnerships with automakers, which produce lower levels of greenhouse gas emissions than conventional vehicles do.

Last week, nuTonomy “passed [its] first driving test” in Singapore, Frazzoli says — meaning its driverless taxis navigated a custom obstacle course, without incident. Now, nuTonomy is planning on testing cars in a business district, called One North, designated for autonomous-vehicle testing. In a few years, Frazzoli says, nuTonomy aims to deploy thousands of driverless taxis in Singapore. The company will act as the service provider to maintain the vehicles and determine when and how they can be operated safely.

But a big question remains: Will driverless taxis put public-transit operators out of work? In Singapore, Frazzoli says, that’s unlikely. “In Singapore, they want to have more buses, but they cannot find people to drive buses at night,” he says. “Robotics will not put these people out of jobs — it will provide more capacity and support that’s needed.”

Importantly, Frazzoli adds, driverless-taxi services used for public transit, such as nuTonomy’s, could promote wider use of electric cars, as consumers won’t need to purchase the expensive cars or worry about finding charging stations. This could have a major impact on the environment: A 2015 study published in Nature Climate Change found that by 2030 autonomous taxis — specifically, more efficient hybrid and electric cars — used worldwide could produce up to 94 percent less greenhouse gas emission per mile than conventional taxis.

Behind the (autonomous) wheel

Frazzoli can’t really say how nuTonomy’s taxis may compare to the likes of Google, Uber, or Tesla, as their technology remains secretive. But nuTonomy’s software — based on research by Frazzoli, nuTonomy’s CEO Karl Iagnemma PhD ’01, and others — includes a few key innovations, he says.  

One such innovation is advanced fleet management, derived from Frazzoli’s previous work writing algorithms to coordinate swarms of drones for the U.S. military. Using similar concepts, Frazzoli, Iagnemma, and nuTonomy’s engineers designed algorithms to allow the minimal number of cars to cart people around a city, alleviating traffic congestion and reducing emissions. In a 2014 paper published in Road Vehicle Automation, Frazzoli and colleagues estimated that 300,000 driverless taxis, in theory, could do the work of the 780,000 traditional taxis currently operating today in Singapore, while keeping waiting times below 15 minutes.

“That’s a 60 percent reduction in the number of vehicles operating in Singapore,” Frazzoli says. “This was a big sign of impact for [the Singaporean] government. At first we were asking them to let us test cars there — then they were asking us to come test.”

The algorithms also function through a “formal logic” that tells the taxis when low-priority “rules of the road” can be broken safely to drive flexibly and efficiently. For example, when driving around a double-parked car, with no oncoming cars, the taxi will see it’s not violating the most important rule — not hitting another object — and pass, Frazzoli says. “These are situations we encounter everyday, and we use our judgment to understand the rules we can violate,” Frazzoli says. “We have these same judgments embedded in our algorithms. … That allows us to exhibit complex behavior and respond in correct way in very many and very complicated scenarios.”

Additionally, Frazzoli says nuTonomy uses LIDAR data in a way that provides more accurate localization — that is, determining where the car is within its environment. All autonomous cars use LIDAR for object detection, but nuTonomy’s system, he says, localizes by detecting not only objects on the road but also stationary objects all around the car. “Even though stuff at road level can change all the time — you can have a car parked here or not, for example — a building is going to stay put,” Frazzoli says.

This has proven beneficial in difficult conditions for driverless cars to navigate. Last year, Frazzoli says nuTonomy successfully tested its vehicles in Michigan, where heavy snow caused whiteout conditions. “There was nothing [visible] on the ground, but who cares — the car was looking at the buildings” for localization, he says.

Going driverless

NuTonomy’s core technology and its connections with Singapore trace back about a decade at MIT. In 2006, Frazzoli joined an MIT team developing an autonomous vehicle for a Defense Advanced Research Projects Agency grant. In 2009, he joined the Singapore-MIT Alliance for Research and Technology (SMART) Future of Urban Mobility project with aims of developing driverless taxis for Singapore.

Over the years, Frazzoli helped develop and test driverless golf carts in a Singaporean public garden through SMART, and teamed up with Iagnemma, who is a principal research scientist in MIT’s Department of Mechanical Engineering and the director of MIT’s Robotic Mobility Group, on other autonomous-vehicle projects. Both Frazzoli and Iagnemma also spent years lecturing far and wide about the benefits of driverless cars, to researchers and automakers.

“But no one was paying attention,” Frazzoli says. “So we figured we need to [develop driverless cars] ourselves.”

In 2013, they launched nuTonomy as an autonomous-car consulting service, before pivoting to a full-fledged autonomous taxi service provider for Singapore last year.

But focusing on Singapore instead of the United States wasn’t just about Frazzoli’s strong ties there: “[Singapore is] concerned with reducing congestion and trying to get the public to use public transportation as much as possible,” Frazzoli says. “At the same time, they’re facing an increase in population by 30 percent within 20 years or so. You cannot keep buying more buses and digging more subway lines. [Singapore] sees [driverless taxis] as a critical vision for their future.”

While developing its driverless taxi fleet, nuTonomy has bootstrapped through small contract projects for automakers. For Jaguar Land Rover, for instance, nuTonomy is developing an autonomous parking feature that will drop off a rider at, say, a shopping center and find its own spot in the parking lot. Such gigs have helped the company grow to 25 employees in Cambridge and Singapore offices, build relationships with the auto industry, and further develop its own software. “Before we get cars driving on the road, we need to be able to park,” Frazzoli says.

As nuTonomy’s driverless taxis in Singapore start getting noticed — along with the those by Google, Uber, and Tesla — Frazzoli anticipates politicians and the public will see the benefits of the technology. “As soon as people start seeing this is real and this is working, and this is the benefit it can provide to the public, then … people will start seeing that this can provide a solution to the mobility problem in big urban centers,” Frazzoli says.

]]> https://robohub.org/how-can-we-use-drones-in-the-humanitarian-and-health-sector/ Fri, 04 Mar 2016 11:24:42 +0000 http://robohub.org/how-can-we-use-drones-in-the-humanitarian-and-health-sector/

Source: TU Delft Ambulance Drone/Youtube

Ever since I watched the exceptional 2013 TED talk by Raffaello D’Andrea on the athletic power of quadcopters I have been fascinated by the possibilities of unmanned aerial vehicles (UAVs) or, as they’re more commonly called, drones. Finally, it felt like the film-like future I dreamed of for 20 years arrived. Since that video, there has been no end to proposals for which they might be used. No sooner had I been discussing with a friend I wanted an autonomous drone to take holiday photos (without going through the usual stop and say ‘cheese’ routine) I stumbled across an advert for Lily, a drone which does just that. If the claims of the Indigogo project ONAGOfly are to be believed, this type of drone will soon be small enough to fit in your pocket and will cost under $200. Oh, you want a Back to the Future style hoverboard? No problem, thanks to drones.

Photography and sports aside, what serious applications might drones have in the imminent future? We already know they are used with devastating effect militarily, but how can they be used for good and what implications can such a versatile machine have in the humanitarian or health sector? For me, they have potential to revolutionise. Here’s why.

Search and rescue

The advantage for drones to be used in search and rescue operations is self evident: using simple commercially available drones with cameras, you immediately have an extremely manoeuvrable eye-in-the-sky (watch the Drone Racing League to see just how manoeuvrable) that can access places previously only accessible by aircraft at a fraction of the cost. Further development of UAVs with the search and rescue brief in mind include the Kwago drone (video below) that incorporates commercial flight awareness and night-time manoeuvrability being a prime example. Whilst running their search and rescue operations in the Mediterranean during 2015, the Migrant Offshore Aid Station were using eye-in-the-sky drones as a means of expanding the radius of their operation.

https://youtu.be/jr3-K4aCNWI

Surveying

Closely linked to this, the use of autonomous drones in surveying provides a genuinely futuristic option to aid organisations. Using geo-referenced photography (or photogrammetry), UAVs are already being used to quickly survey and produce large 2D and 3D maps of astounding accuracy — particularly within the agriculture and construction industry. However, it is easy to envisage how such tools could be used by humanitarian actors within emergency or refugee situations — for example, a detailed survey of a refugee camp could be conducted by a single person and UAV in a matter of hours, and in addition, this could be updated at regular intervals with minimum additional work. The non-profit Drone Adventures is doing just this; having worked in Haiti with the International Organisation on Migration on 3D mapping for flood prevention (video below); and with MEDAIR in the Philippines on surveying areas affected by Typhoon Haiyan.

HumanITas Solutions is another organisation that has foreseen the potential or UAV surveys in humanitarian work and is about to release a virtual environment to utilise this. Using UAVs that carry commercial smartphones and tablets instead of specialist equipment, their software works as an operating system specifically focused for humanitarian teams. With their android or OS app turned on, the phone can be fixed to the drone and sent to autonomously map areas — working alone or in tandem with other drones — using GPS and photography, by stitching these images together, complete maps and 3D models can be quickly collected. The software then allows for annotation, collaboration and import/export with other teams. The beauty of this system is the use of conventional equipment — understanding that often getting experts quickly to disaster zone can be difficult. Check out the video below:

As with all innovation, technology is the deciding factor on feasibility. The Swiss Foundation for Mine Action (FSA) has been using drone observation in mine detection for many years, for obvious reasons. Though not there yet, there are projects which aim to mount instruments — such as thermal imaging — on the drones they fly over suspected minefields, providing and invaluable resource in the fight against civilian deaths. This doesn’t seem like an unreasonable goal: drones that can map radiation already exist, whilst there is a renewed interest in using drones for gas detection after a recent leak in California.

As surveying becomes more widespread, so too the technology is improving. A new startup, Nomoko, claims to have built a 1,000 mega pixel camera that, if mounted on a UAV, could map huge areas to 1cm accuracy in a fraction of the time it currently takes — the company claims that 10,000 drones mounted with its camera could map the world at this accuracy in just 60 days at a cost of around $100 million. Currently, a single satellite will set you back at least this amount and would take two years to achieve the task at a much lower resolution. Beyond just being a nice sales pitch, such accuracy could allow the data to be used in the search for survivors after a natural disaster by comparing photos taken of the same scene at short, regular intervals.

Drones as delivery tools

UAVs are evidently well-equipped to access difficult terrain, and this is something that Médecins Sans Frontières (MSF) exploited when conducting a trial of a UAV delivery system for lab samples. Traditional microscopy tuberculosis (TB) testing requires sputum samples to be tested within three hours to be valid, (newer GeneXpert sampling allows 3 days) but such a time-constraint was inhibiting in remote and inaccessible locations such as Gulf Province; a swampy region in Papua New Guinea, to which ‘normal’ access by car took four hours. With the UAVs, delivery times were slashed to just one hour. The trial was successful — as was acceptance by the local population — and such a system could provide an excellent means to improve infectious disease surveillance when time is of the essence. Could such a system improve the emergency response to viruses such as Lassa or Ebola, where quarantine is necessary? Could a suspected case be quarantined in their home whilst an UAV carrying samples is dispatched to see if bringing them to a health facility is really necessary?

Drones could also facilitate speedy delivery in the opposite direction. Again, UAVs almost always offer a cheaper alternative to conventional aircraft. Capitalising on this for cold-chain products seems like an obvious move. Of course, the tech is the limiting factor: battery life and payload are preventing goods of reasonable size being delivered any meaningful distance. However, future developments could change this: solar-powered drones are one option or drones with combustion engines another. What about UAVs that can automatically dock with charging stations (possibly solar powered) along a set route? Effectively hopping from one station to the next as far as required…

The SaveME smartphone UAV, uses a quadcopter frame to transport a smartphone and can be used to find help in the event of being trapped. However, it is also proposed as a tool for prescription collection. In the future, could sending your drone to the local pharmacy to collect your prescription become the norm when you are too ill to leave your house? All interesting proposals and one specifically targeting the delivery of medical supplies in the humanitarian sector was recently proposed by Norman Foster. The notion of delivery is starting to be explored with a more specialised health focus in two areas: organ harvest and cardiac arrest.

Drones in emergency response

There are few medical situations where time is more imperative than organ transplant — a heart can only survive for 4-6 hours outside the body so, in order to be matched to a recipient with the same blood type, body size and geographic location, the process must occur very quickly. Research has shown that, though for the victim there is no clear medical advantage to air ambulance over ground ambulance for arrival on the scene, the air evacuation did provide more organs than traditional ground units. Could drones offer the paramedics on the scene the tool to harvest and send organs on a par with the system of getting the organs to the hospital by air within the urgent time window?

Cardiac arrest is another situation where time is of the essence. In cases where defibrillation is the only thing that can revive someone, drones might again provide the answer. Alec Momont, a Dutch engineering student, has proposed mounting a defibrillator on a UAV which can lock on to the GPS of the smartphone making the emergency call and arrive on the scene on minutes. The idea is particularly bright because modern defibrillators operate automatically and just require correct attachment to the victim’s body — something that the caller could easily do with guidance. Though they are appearing much more frequently around cities in Europe, a rapidly deployable defibrillator could provide an invaluable service in suburban areas on the outskirts of places with many public buildings. The project created a prototype, and the video, but it has yet to be developed further.

Vector control

A key process in health development remains vector control. Prevention of malaria, dengue or Zika, relies on limiting their vector: mosquitos; be it through sterilisation, environmental measures or fumigation — as Bill Gates famously wrote, the mosquito is the deadliest creature in the world, being ultimately responsible for 725,000 deaths per year. One drone project — MosquitoCopter — is targeting this problem through the sterilisation route. By releasing sterilised male mosquitos, who will mate with the blood-sucking females and prevent propagation, the mosquito population can be significantly reduced. As with most such projects, the problem becomes accessing the affected areas — MosquitoCopter, does this with a manoeuvrable quadcopter that can be programmed to follow a set route, automatically releasing the sterilised mosquitos at set intervals. A similar concept is also being used to support the Southern Tsetse Eradication Project in Ethiopia — though in this case, the drones are larger and can cover an area of 100km2 per flight. Even at a more basic level, UAVs can help by identifying mosquito breeding sites for direct action and are already being put to good use in Brazil to combat Zika.

Future hurdles

As with all new technology, UAVs are undergoing a delicate phase right now: simply put, governments and regulators don’t yet know how to deal with them in terms of safety (i.e. plane collisions etc.) or security (someone recently mounted a hand gun on a UAV). The regulation of drones therefore, will change drastically in the coming few years and determine their prevalence in our everyday lives. It’s worth noting that UAVs pose a challenge to the control of governments over our skies — an area that has, until this point, has maintained a miraculous safety record through very strict controls — so new challengers to that can be seen as a threat. The Federal Aviation Authority’s legal pursuit of Raphael Pirker, a Swiss drone pilot who was fined $10,000 for making a promotional video using a drone, is a prime example of the confusion and delicate politics surround this emerging area.

In the US and Europe, much of the regulation is in the testing phase, largely pushed by the development of delivery drones in the commercial sector. Last year, testing licenses were issued to a number of projects including a small startup delivering medical supplies to rural communities in Virginia. These small projects will mainly serve to inform regulatory legislation, which will then likely be the foundation in other countries. Amazon is one of the most vocal advocates for the use of commercial drones and the company’s influence will play a huge part in deciding the future of commercial drones. This influence isn’t going unnoticed: in 2015, the internet giant spent $10 million on lobbying in Washington and one suspects that its Prime Air service had a lot to do with this sharp increase. In fairness to the regulators, the proposals by Amazon will (if the video below is to be believed) fundamentally alter the skies over the US and Europe, so proceeding with caution does not seem unreasonable. Once permission is granted, the chances of it being revoked are much smaller.

It’s difficult to envisage exactly how this regulation will play out in developing countries and thus affect the humanitarian possibilities of drones. In the wake of natural disasters, their implementation will almost definitely become a necessity in coordinating the humanitarian response, but particularly in conflict zones, flying UAVs could have negative consequences for aid agencies who wish to avoid association with warring parties. Just the term ‘drone’ itself can conjure images of the US military’s Predator drones, which do look rather similar to some UAVs already being used in vector control. Such associations have already led MSF to reject their use in conflict zones. There have also been cases of the data being collected for humanitarian purposes also being used for law enforcement: a point that could in the future severely damage aid organisations’ reputation for neutrality if similar events occur in conflict zones. It seems probable however, that as the use of UAVs become far more widespread, their possible military connotations will be lessened. In terms of acceptance by the local population, existing humanitarian UAV projects have all seemed to show that, as long as they are well informed about the project and how the drones work, this is not a problem.

A 2014 report by OCHA did try to consider some of the wider issues and possible applications for UAVs in the humanitarian sector, but the technology is moving so fast, this is already largely outdated. The FSA is currently trying to update and consolidating the existing knowledge on drone projects in the humanitarian sector as a means to increase awareness of the UAV tools available to aid workers and to propose guidelines for UAV use in the field.

The final hurdle for the adoption of such useful technologies is cost. Professional UAVs are not cheap, and the hardware and software for a project like those run by Drone Adventures would cost around $20,000 and there are maintenance and repair costs to factor in to that, plus training. Other issues such as drone malfunction or hijack could also prove costly for organisations using drones for humanitarian purposes.

Conclusions

Having explored a range of possibilities for UAVs in the health and humanitarian sector, it seems clear that the coming decade will bring with it an extraordinary amount of change — in no small part due to drones. Their obvious benefit as search and survey tools will probably be their first point of mass use. With improvements to battery life and payload weight, delivery will quickly become important too and projects such as the TB sample delivery should be capitalised upon. The use of more autonomous drones will no doubt go in directions currently impossible to imagine, and this is exactly why UAVs are so exciting: they offer a blank canvas on three axes upon which anyone can imprint their ideas.

Originally posted innovatinghealth.eu/blog

]]> https://robohub.org/robocar-news-from-ces-2016/ Wed, 13 Jan 2016 16:09:11 +0000 http://robohub.org/robocar-news-from-ces-2016/ I’m back from CES 2016 with a raft of news, starting with robocars. Some news was reported before the show but almost everybody had something to say — even if it was only to have something to say!

I have many more photos with coverage in my CES 2016 Photo Gallery.

Ford makes strong commitment

Ford’s CEO talks like he gets it. Ford did not have too much to show — they announced they will be moving to Velodyne’s new lower cost 32-laser puck-sized LIDAR for their research, and boosting their research fleet to 30 vehicles. They plan for full-auto operation in limited regions fairly soon.

Ford is also making its own efforts into one-way car share (similar to Daimler Car2Go and BMW DriveNow) called GoDrive, which pushes Ford more firmly into the idea of selling rides rather than cars. The car companies are clearly believing this sooner than I expected, and the reason is very clearly the success of Uber. (As I have said, it’s a mistake to think of Uber as competition for the taxi companies. Uber is competition for the car companies.)

Ford is also doing an interesting “car swap” product. While details are scant, it seems what the service will do is let you swap your Ford for somebody else’s different Ford. For example, if somebody has an F-150 or Transit Van that they know they won’t use the cargo features on some day or weekend, you drive over with your ordinary sedan and swap temporarily for their truck — presumably with a small amount of money flowing to the more popular vehicle. Useful idea.

The big announcement that didn’t happen was the much-rumoured alliance between Ford and Google. Ford did not overtly refute it but suggested they had enough partners at present. The alliance would be a good idea, but either the rumours were wrong, or they are waiting for another event (such as the upcoming Detroit Auto Show) to talk about it.

Faraday Future, where art thou?

The big disappointment of the event was the silly concept racecar shown by Faraday Future. Oh, sure, it’s a cool electric racecar, but it has absolutely nothing to do with everything we’ve heard about this company, namely that they are building a consumer electric car-on-demand service with autonomous delivery. Everybody wondered if they had booked the space and did not have their real demo ready on time. It stays secret for a while, it seems. Recent hires, such as Jan Becker, the former head of the autonomous lab for Bosch, suggest they are definitely going autonomous.

Mapping heats up

Google’s car drives by having super-detailed maps of all the roads, and that’s the correct approach. Google is unlikely to hand out its maps, so both Here/Navteq (now owned by a consortium of auto companies in Germany) and TomTom have efforts to produce similar maps to licence to non-Google robocar teams. They are taking fairly different approaches, which will be the subject of a future article.

One interesting edge is that these companies plan to partner with big automakers and not just give them map data but expect data in return. That means that each company will have a giant fleet of cars constantly scanning the road, and immediately reporting any differences between the map and the territory. With proper scale, they should get reports on changes to the road literally within minutes of them happening. The first car to encounter a change will still need to be able to handle it, possibly by pulling over and/or asking the human passenger to help, but this will be a very rare event.

MobilEye has announced a similar plan, and they are already the camera in a large fraction of advanced cars on the road today. MobilEye has a primary focus on vision, rather than Lidar, but will have lots of sources of data. Tesla has also been uploading data from their cars, though it does not (as far as I know) make as extensive use of detailed maps, though it does rely on general maps.  read more »

]]> I’m back from CES 2016 with a raft of robocar news, some of which was reported before the show. Almost everybody in the robocar space had something to say — even if it was only to have something to say! I have many more photos with coverage in my CES 2016 Photo Gallery.

Ford makes strong commitment

Ford’s CEO talks like he gets it. Ford did not have too much to show — they announced they will be moving to Velodyne’s new lower cost 32-laser puck-sized LIDAR for their research, and boosting their research fleet to 30 vehicles. They plan for full-auto operation in limited regions fairly soon.

Ford is also making its own efforts into one-way car share (similar to Daimler Car2Go and BMW DriveNow) called GoDrive, which pushes Ford more firmly into the idea of selling rides rather than cars. The car companies are clearly believing this sooner than I expected, and the reason is very clearly the success of Uber. (As I have said, it’s a mistake to think of Uber as competition for the taxi companies. Uber is competition for the car companies.)

Ford is also doing an interesting “car swap” product. While details are scant, it seems what the service will do is let you swap your Ford for somebody else’s different Ford. For example, if somebody has an F-150 or Transit Van and they know they won’t use the cargo features on particular day, you could drive over with your ordinary sedan and temporarily swap it for their truck — presumably with a small amount of money flowing to the more popular vehicle. Useful idea.

The big announcement that didn’t happen was the much-rumoured alliance between Ford and Google. Ford did not overtly refute it, but suggested they had enough partners at present. The alliance would be a good idea, but either the rumours were wrong, or they are waiting for another event (such as the upcoming Detroit Auto Show) to talk about it.

Faraday Future, where art thou?

The Faraday Future concept electric racecar is cool, but seems to be completely at odds with everything we had heard about what FF was up to. Photo credit: Brad Templeton

The big disappointment of the event was the silly concept racecar by Faraday Future. Oh, sure, it’s a cool electric racecar, but it has absolutely nothing to do with everything we’ve heard about this company: namely, that they are building a consumer electric car-on-demand service with autonomous delivery. Everybody wondered if they had booked the space and did not have their real demo ready on time. Their plans will stay secret for a while, it seems, though recent hires such as Jan Becker (former head of the autonomous lab for Bosch) suggest they are definitely going autonomous.

Mapping heats up

Google’s car drives by having super-detailed maps of all the roads, and that’s the correct approach in my opinion. Google is unlikely to hand out its maps, so both Here/Navteq (now owned by a consortium of auto companies in Germany) and TomTom are working to produce similar maps to licence to non-Google robocar teams. They are taking fairly different approaches, which will be the subject of a future article.

One interesting edge is that these companies plan to partner with big automakers and not just give them map data but expect data in return. That means that each company will have a giant fleet of cars constantly scanning the road, and immediately reporting any differences between the map and the territory. With proper scale, they should get reports on changes to the road literally within minutes of the changes occurring. The first car to encounter a change will still need to be able to handle it — possibly by pulling over and/or asking the human passenger to help — but this will be a very rare event.

MobilEye has announced a similar plan, and they are already the camera in a large fraction of advanced cars on the road today. MobilEye’s primary focus is on vision (rather than LIDAR), but it will have lots of sources of data. Tesla has also been uploading data from their cars, though it does not (as far as I know) make such extensive use of detailed maps, even though it relies on maps generally.

Google is the world’s number one mapping company, and thanks to the hundreds of millions who drive with Android phones, it has tremendous access to data on the speed patterns of cars. But here is one area that Google might lose out on: the partners of Here and TomTom may have a lot more cars scanning the road than Google will have for some time, even if the scans are not as advanced.

Of course, Apple also has a mapping division, and plans to enter this space. And the “Navigation Data Standard” consortium is trying to build a standard format for advanced map data so robocar systems an easily switch between map vendors. Lots of competition is good for the public.

Nvida makes a huge push to be the platform

NVIDIA’s software suite was shown off. Here we see not the localization but the their computer vision system tagging cars and trying to identify them. Photo credit: Brad Templeton

NVIDIA, which makes the graphics chips in most of your computers, has increased their already large push in this area. GPUs are today’s supercomputers, and NVIDIA is promoting their new Drive PX2 board, which features multiple GPS and other processors to effectively create a supercomputer for use in cars. All this computing power then gets applied to computer and machine vision, particularly systems trained with convolutional neural networks like Deep Learning, to try to do the many tasks needed in a self-driving car: localization, sensor fusion, perception and motion planning. NVIDA’s bet is that general purpose super-high-powered computing is more useful for this task than the specialized vision processing hardware that MobilEye makes, and that it can probably all be made to work from cameras, without LIDAR. (Though to be fair, NVIDIA is not as anti-LIDAR as Elon Musk or MobilEye, saying that their supercomputers and software will still be valuable combined with LIDAR.) One of the NVIDIA demos in pedestrian detection combined a Quanergy 8 plane LIDAR and their camera systems. In the demo, they used water jets to simulate rain, to show that in wet conditions, it is the vision that fails and the LIDAR that keeps detecting the pedestrians. Quanergy’s LIDAR is able to distinguish between signal returns from raindrops (which are more dispersed) and those coming off of solid objects.

NVIDIA isn’t the only chip company with an interest, but it is the most advanced. NXP and Qualcomm both had tech on display (mostly along the theme of the “connected car”), as did Intel and a few others, such as OS company QNX (a unit of Blackberry founded by classmates of mine in Canada). Other chip companies have been making efforts towards the ADAS market (such as Intel, TI and CEVA) and the huge success of MobilEye there will draw in more companies seeking to be suppliers for robocars.

New entrants — VF and IAV

Just about every player out there has something in the space now. German Tier One VF was showing both existing parts (such as electric steering motors and ADAS tools) as well as complete systems for OEMs not wanting to do the work themselves.

The most silly demo in the parking lots came from a partnership of IAV, Microsoft and some others. In this demo, the car would drive a test course towards a light where a pedestrian was waiting, hidden behind an SUV. The pedestrian’s Microsoft wristband was sending her GPS coordinates up to a server, which then sent them down to a traffic light. The traffic light was then able to use DSRC (V2V/V2I) to tell the car about the pedestrian, as well as the green/red state of the light. Upon learning this, the car would slow down as it passed the parked SUV.

It seems reasonable at first, but even the demonstrators agreed that it’s not practical for cars to always slow down every time a pedestrian is close to the street. In addition, the odds that people will be constantly uploading their location from wristbands or phones — even if GPS were accurate enough for this — will be pretty low for years to come.

Here is an Engadget article on the demo.

Toyota’s billion dollar bet on AI

Two wacky Toyota concept vehicles. I could not figure the small one: it banks, but it does not seem to have a place for a person even though it is not meant for cargo. Photo credit: Brad Templeton

The strange concept cars seen here in the Toyota booth were not the real Toyota story at CES. Far more interesting is the creation of a new AI research lab inside Toyota with a $1 billion budget, run by Gill Pratt, who also ran the DARPA Robotics Challenge I reported on last year. That’s a huge budget, and will fund some pure research as well as researched aimed at driving.

New Quanergy Lidar announced

For full disclosure, I am on the advisory board in Quanergy and own stock, but I was pleased to see the announcement (ahead of schedule) of Quanergy’s first solid state LIDAR, an 8 line phased-array LIDAR with a 120 degree field of view. While 8 planes is on the low end for self-driving, several of these LIDARS can be combined at this low price. The LIDAR will also help boost smaller robots indoors and out. Those who dismissed LIDAR as overly expensive have, as I have predicted, made a mistake.

Quanergy has partnered with Delphi to market the LIDAR to automakers.

New Velodyne and Valeo Lidars

Valeo showed off the low cost 4 plane LIDAR they are making based on IBEO’s original product. It’s $250. Photo credit: Brad Templeton

Quanergy wasn’t the only LIDAR being promoted. Velodyne, which makes the expensive but powerful 64-laser LIDAR used in many research cars (including Google’s before they built their own) has a new unit that is the size of a large puck with 32 lasers. It’s going to be used in Ford’s new research cars, among others. Cost was not named, but will be under $10,000 — the current cost of Velodyne’s 16-laser LIDAR. It is claimed to be solid state, but no details are available on how it works.

Valeo is now in production on the $250 4-laser LIDAR based on designs from IBEO. They have branded it SCALA, and while it will primarily be used in the ADAS market, they are hoping for even more.

While not related to robocars, Valeo also showed off their Sightstream product, which replaces side-view mirrors with cameras and screens. Today, the regulations demand side-view mirrors — they are even on Google’s steering-wheel-free 3rd generation car — but they cause a lot of drag and get hit in accidents, vendors have wanted to replace them with cameras for a while. Cameras are superior in many ways, not the least of which is that they don’t have blindspots.

Nissan promises 10 models with autonomy

Nissan was not at CES, but their CEO held a press conference at Nissan’s research lab in Sunnyvale to divert some attention. He promised Nissan will put autonomous drive features into 10 different Nissan models, without naming them. By about 2018 you can expect autopilot functions (like you see in Tesla and others), and by 2020 you can expect some greater level of autonomy — possibly the standby supervision approach incorrectly called Level 3 by NHTSA/SAE.

Nissan has been a leader in the Japanese market, but Toyota’s new AI efforts may push it ahead. Honda, Mazda and Subaru continue to show very little in the way of effort.

Nissan has made the statement that it does not want to embrace car-sharing like Uber, Lyft and robotaxis, but instead wants to focus on cars aimed at single owners. I judge that an error, but we’ll see.

Tesla car summon

You have to hand it to Elon Musk for bravado, claiming that in two years he will have fully capable unmanned-level autonomy. The other day he said:

“Within two years you’ll be able to summon your car from across the country, ” Musk said on Sunday in a teleconference with the media, adding that “ I might be slightly optimistic on that.”

 

He went to to say that you might be in New York and summon your Tesla from Los Angeles. I’m a big fan of this concept (I call it the “whistlecar”) but he is indeed a bit optimistic, if for no other reason that it almost surely won’t be legal for an unmanned car to cross the country in two years.

Reaching the safety levels for unmanned operation on a wide array of streets in 2018 is also a big challenge, especially without a LIDAR. More on that, later.

Audi says little

Audi’s self-driving efforts have been quite significant, but at CES they only reaffirmed their commitment to self-driving systems without adding anything concrete. Audi, which is part of VW, is reeling from the emissions scandal. Will customers trust them and their software?

 

BMW shows a concept

BMW’s concept car with 3 driving modes: manual, assisted and autonomous. Not that it could actually do that — it was just there to look cool. Photo credit: Brad Templeton

BMW has long been one of the leaders among big car companies, in spite of the irony of them building the “ultimate non-driving machine.” This year they mostly went the imaginary concept route, displaying a futuristic car and claiming it had “3 modes” — manual, assisted and self-driving. But the car didn’t actually do those things and the only real demo was some self-parking outside. (Last year they had the BMW i3 cars available for test drive, and the unmanned cars rolled up to you for your test drive on a special course.)

Concept cars like this (meant only to express possible future ideas) are common at car shows, but at CES they seem bizarrely out of place. To the electronics crowd, they make no sense — they are vapourware at best, and pointless at worst. Why show a product you have no intention of building? The CES audience accepts (and likes) seeing pre-release products, but wants to know what BMW is actually doing.

For more coverage, including non-car coverage, check out my CES 2016 Photo Gallery.

 

This post originally appeared on robocars.com.

]]> https://robohub.org/the-drone-centers-weekly-roundup-113015/ Mon, 30 Nov 2015 18:38:33 +0000 http://robohub.org/the-drone-centers-weekly-roundup-113015/ Read more →

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A Hermes 900 flying as part of the Swiss evaluation campaign in 2012. Credit: armasuisse

At the Center for the Study of the Drone

This fall season has been a busy one for the drone industry, and, for some a very lucrative one. The past few months have seen a spike in the sale of military unmanned systems, especially U.S. technologies that were previously restricted for export, while the commercial industry has seen a number of bold moves from startups and established industry leaders alike as market competition heats up. Here’s what you need to know.

News

A U.S. drone strike in Afghanistan reportedly killed Khan Sayed, a commander of a breakaway faction of the Pakistani Taliban. The strike took place in Khost Province, near the border with Pakistan. At least 12 other militants are believed to have been killed in the strike. (New York Times)

Switzerland concluded a deal with Israeli drone manufacturer Elbit Systems to purchase an unspecified number of Hermes 900 drones, a medium-altitude, long-endurance unmanned reconnaissance aircraft. The $200 million deal will be fulfilled over four years. (Reuters)

Meanwhile, the Department of Defense announced that Boeing Insitu has won a $70.9 million contract to supply the government of Afghanistan with ScanEagle surveillance drones. The 65 ScanEagle aircraft and supporting equipment will be delivered by June 2018. (Press Release)

A U.S. MQ-9 Reaper drone reportedly crashed near Bagram Air Field in Afghanistan. The aircraft, which was based out of Kandahar, was completely destroyed, but no individuals on the ground were injured in the accident. The causes of the crash are under investigation. (Stars and Stripes)

A panel of judges for the Court of Appeals for the Second Circuit ruled that the Department of Justice does not have to release memos on the legal basis for U.S. drone strikes. The ruling is the latest development in a lengthy battle by the American Civil Liberties Union and the New York Times to force the Justice Department to reveal more information about the targeted killing campaign. (New York Times)

A man was ticketed in New York for flying a drone over the Macy’s Thanksgiving Day Parade. The man, a tourist from Russia, told police that he was not aware of the rules against drone flights. (NBC New York)

An 18-month-old lost an eye after being struck by a drone in Worcestershire, England. The incident occurred after a nearby drone hit a tree, causing it to spin out of control. (The Telegraph)

Commentary, Analysis, and Art

In a lecture at the Royal United Services Institute, former Gen. Stanley McChrystal said that the bases from which operators fly drones in the U.K. could be targeted by ISIS militants. (The Guardian)

At TechRepublic, Hope Reese speaks with the chief of police for West Fargo, North Dakota about how drones may affect law enforcement.

At the New York Times, Cecilia Kang takes a look at how airspace regulators are rushing to implement drone rules before the holiday season.

At Just Security, Brett Max Kaufman analyzes the Court of Appeals’ decision not to order the release of the Department of Justice memos.

At the Art of Future Warfare, Marika Landau-Wells explains the inspiration behind her short story on the life of a drone operator.

At Wired, Matt Simon reviews the Drone World Expo, an event in California that featured dozens of drone manufacturers, businesses, and enthusiasts.

At the Wall Street Journal, Newley Purnell and Jack Nicas write that DJI, the manufacturer of popular commercial drones, is looking to build drones that appeal to farmers.

At the Los Angeles Times, W.J. Hennigan reports that military contractors are taking a larger role in operating U.S. drones to make up for a shortage in Air Force personnel.

At Lawfare, Zoe Bedell offers a few takeaways from the FAA’s proposed drone registration requirements.

At Haaretz, Amitai Ziv profiles an Israeli video company that avoided bankruptcy by turning to manufacturing drones.

A Stratfor report examines the promise and challenges of commercial drones and the pace of regulations in countries around the world.

At Breaking Defense, Sydney J. Freedberg Jr. takes a look at the challenges faced by the U.S. Navy’s new chief of unmanned systems.

Know Your Drone

U.K. Prime Minister David Cameron has announced plans to field a high-altitude long-endurance surveillance drone for surveillance operations. Though Cameron did not mention the drone by name, it is thought to be the Airbus Zephyr solar-powered unmanned aircraft. (IHS Jane’s 360)

Meanwhile, Spanish officials have confirmed plans to eventually weaponize the military’s future fleet of MQ-9 Reaper drones. (Flightglobal)

NASA is developing an unmanned helicopter to take aerial photos of Mars. (NPR)

A U.S. Air Force experimental X-56A drone, which is being used to develop ways of suppressing aeroelastic instability, crashed during a test in California. (Air Force Technology)

The U.S. Marines have placed a $13 million order for a new batch of Puma AE tactical surveillance drones. (GPS World)

The Guardian takes a close look at U.S. drone company PrecisionHawk’s efforts to develop a cellular network-based air traffic control system for drones.

Quartz profiles the Cheerson CX-10, a $14 hobby drone.

Drones at Work

The U.S. Agency for International Development is considering using drones to deliver emergency medical supplies to remote areas in Ethiopia. (Drone360)

The state government of New South Wales in Australia has deployed small drones in an attempt to prevent shark attacks. (The Guardian)

The European Maritime Safety Agency and the European Space Agency are hoping that drones will be useful in identifying ships that don’t comply with emissions limits. (Wall Street Journal)

Police in Dorset, England are testing whether drones could help aid law enforcement work. (BBC)

Meanwhile, first responders in eastern Ontario, Canada are using drones in a variety of life-threatening situations. (CBC)

The University of Manchester and Britain’s Environment Agency are using drones to monitor emissions levels from landfills. (BBC)

Cape Productions, an aerial photography company, has partnered with some U.S. ski resorts to create dedicated areas where skiers can pay for high-quality video of their exploits. (Orange County Register)

Secom, a Japanese security firm, will offer customers the capability track suspicious individuals or vehicles by using aerial drones. (Nikkei Asian Review)

A disaster recovery team in New Zealand used a drone to survey the site of a helicopter crash on Fox Glacier. (Radio New Zealand)

The Weekly Drone Roundup is a newsletter from the Center for the Study of the Drone. It covers news, commentary, analysis and technology from the drone world. You can subscribe to the Roundup here.

]]> https://robohub.org/robohub-digest-0915-big-brands-cozy-up-to-robots/ Tue, 06 Oct 2015 02:05:20 +0000 http://robohub.org/robohub-digest-0915-big-brands-cozy-up-to-robots/
A quick, hassle-free way to stay on top of robotics news , our robotics digest is released on the first Monday of every month. Sign up to get it in your inbox. 

 

Who’s driving?

Former DARPA Program Manager Gill Pratt will direct Toyota’s new $50M robotics research investment

Auto giant Toyota announced that it will invest $50 million to develop “advanced driving support” technology in partnership with MIT’s CSAIL and Stanford’s SAIL, and has hired Former DARPA Program Manager Gill Pratt as their new Executive Technical Advisor to direct the project. And Google announced former Hyundai CEO John Krafcik as its new self-driving car chief executive, a decision that could take this Google’s research enterprise one step closer to becoming an actual business.

Meanwhile, ride share service Uber hired two security experts — Charlie Miller from Twitter and Chris Valasek from IOActive, who in July demonstrated they could hack a moving Jeep — to join the growing team of researchers at their company’s Advanced Technologies Center in Pittsburg, notorious for having recruited dozens of experts from Carnegie Mellon University’s robotics department.

All the corporate interest would suggest that the technology is rapidly maturing, but is it a good thing for basic research? While the New York Times Magazine speculates whether high tech academia can survive poaching from Silicon Valley, others suggest that there will always be a need for early stage research that only university labs can cater to.

 

Cleaning up

What does the VW scandal mean for robocars?

Volkwagen made headlines when it was discovered that millions of their vehicles used software to cheat during emissions tests. Unfortunately this was not the first time an automaker used software to break the law. Brad Templeton muses on what the scandal means for the future of robocars.

On a tidier note, Volvo announced it would team up with the Chalmers University of Technology, Mälardalen University of Sweden, Penn State, and recycling company Renova to develop a new project called Robot-based Autonomous Refuse handling (ROAR). The hope is to have supervised robots collecting your garbage soon.

Meanwhile Peloton Technology, a developer of adaptive cruise control systems for trucks, cleaned up when they secured $17 million from several strategic investors, including Japanese robot maker Denso.

 

Retailing robots

Using a BeamPro, Brianna Lempesis waits in line to buy an iPhone6s from the Apple Store in downtown Palo Alto. Photo: Suitable Technologies.

While department store giant Target announced plans to test robot workers in its upcoming concept store, Chloe the robot has already started work at Best Buy in New York city, and in San Francisco, at a fully automated restaurant called Eatsa, guests can order their meal via in-store iPads and collect their food from small glass compartments with no human staff in sight.

And robots aren’t just working behind the counter these days. This September shoppers used telepresence devices to queue up at their local Apple stores to buy the newly released iPhone 6S.

 

Talking robots

IBM’s Rob High chats with Nao during RoboBusiness 2015 keynote.

Mattel, manufacturer of the iconic Barbie doll, is planning to use AI to help conversational dolls to get to know their human playmates. Every little girl’s dream? Maybe, but critics have already raised concerns about the talking doll’s impact on privacy and gender perceptions.

Meanwhile, the makers of Jibo are working hard to make their social robot sound lifelike, and a chatbot named Rose came out tops to win the Loebner artificial intelligence prize despite not convincing the judges she was actually human.

The push towards conversational systems should not come as a surprise to anyone who attended RoboBusiness this year. In the keynote talk, IBM‘s Robert High posited that “Cognitive computing will be to computing what transaction processing is today.”  (Check out more Robobusiness coverage, including Rethink’s Sawyer and the new OTTO from Clearpath here).

 

Winners’ circle

Cleverpet wins the 2015 Robot Launch international startup competition.

The Robot Launch international startup competition announced its winners this September. CleverPet’s smart pet feeder took first prize, with judges citing the how product’s adaptability and focus on play distinguished it from other robotic pet products. First runner up was Preemadonna’s Nailbot — a robot that lets you paint custom designs on your fingernails.

euRathlon 2015 Grand Challenge Winners

Meanwhile in Europe, euRathon — the world’s first outdoor land, sea and air disaster competition — came to an end. Using teams of land, air and sea robots, participants were required to locate missing workers, map a building and identify critical hazards, and inspect land and underwater pipes and stem a leak, all within 100 minutes. The multi-domain partnership Cobham (land), Universitat de Girona (sea) and ISEP/INESC TEC (Air) were crowned Winners of the Grand Challenge.

 

Fast moving prosthetics

Jason Barnes, an amputee drummer who tours nationwide by playing with a robotic arm.

Robotic prosthetics are fast becoming one of the most exciting developments in rehabilitation, giving hope to thousands of amputees. This was beautifully demonstrated in a short documentary exploring the life of ‘cyborg drummer’ Jason Barnes.

If you think those drumsticks are moving fast, so is the research. A hand developed at Johns Hopkins using DARPA technology gives its wearer sense of touch, and researchers from CNIB and EPFL have developed a brain-controlled prosthetic that learns from its mistakes, adapts to changing conditions, and speeds up the prosthetic training process for patients.

 

Hot and bothered

Nothing will generate headlines like sex. Except maybe robots and sex.

This September robot sex hit the news when robot ethicist Kathleen Richardson launched the Campaign Against Sex Robots. Drawing parallels between robot sex and prostitution, Richardson argued that sexbots reinforce asymmetrical relationships and could exacerbate gender inequalities. Others disagreed, arguing that fringe sex toys could hardly doom all of humanity to exploitation and empty relationships, and that they may offer a safe environment for fulfilling sexual fantasies.

Then, just when we thought the topic was going limp, a paper titled ‘The Future of Sex Report’ stoked the fire again by claiming that by 2050, people will be having more sex with robots than with each other.

All this pillow talk was clearly too much for some: SoftBank reportedly issued a clause in their purchasing contract that bans users from having sex with Pepper, and Malaysian authorities withdrew their support for the Love and Sex with Robots conference, which was planned for November.

Want tease out the finer points of the debate? Check out the Robot-Human Love episode from the Robots Podcast.

 

Events to watch for this October:

• RoboUniverse Tokyo – Tokyo, Japan – Oct 7-11
• Maker Faire Pittsburgh – Pittsburgh, PA, USA – Oct 10-11
• Maker Faire Seoul – Seoul, South Korea – Oct 10-11
• National Robot Safety Conference – Pittsburg, PA, USA – Oct 12-14
• International Collaborative Robots Workshop – Pittsburg, PA, USA, Oct 25
• Maker Faire Rome – Rome, Italy – Oct 16-18
• Robotics Innovation Show – London, UK – Oct 20-21
• International Conference of Social Robots in Therapy and Education – Almere, Netherlands – Oct 22-23
• International Conference on Social Robotics (ICSR) – Paris, France – Oct 26-30
• Field and Assistive Robotics 9 – Lahore, Pakistan – Oct 30 – Nov 1

 

Miss a previous digest? Don’t worry! Check out our archives. 

]]> https://robohub.org/what-does-the-vw-scandal-mean-for-robocars/ Mon, 05 Oct 2015 14:53:37 +0000 http://robohub.org/what-does-the-vw-scandal-mean-for-robocars/ Most of you would have heard about the giant scandal where it has been revealed that Volkswagen put software in their cars to deliberately cheat on emissions tests in the USA and possibly other places. It’s very bad for VW, but what does it mean for all robocar efforts?

You can tons about the Volkswagen emissions violations but here’s a short summary. All modern cars have computer controlled ignition systems, and these can be tuned for different levels of performance, fuel economy and emissions. Cars have to pass emission tests, so most cars have to tune their systems in ways that reduce other things (like engine performance and fuel economy) in order to reduce their pollution. Most cars attempt to detect the style of driving going on, and tune the engine differently for the best results in that situation.

VW went far beyond that. Apparently their system was designed to detect when it was in an ignitions test. In these tests, the car is on rollers in a garage, and it follows certain patterns. VW set their diesel cars to look for this, and tune the engine to produce emissions below the permitted numbers. When the car saw it was in more regular driving situations, it switched the tuning to modes that gave it better performance and better mileage but in some cases vastly worse pollution. A commonly reported number is that in some modes 40 times the California limit of Nitrogen Oxides could be emitted, and even over a wide range of driving it was as high as 20 times the California limit (about 5 times the European limit.) NOx are a major smog component and bad for your lungs.

It has not been revealed just who at VW did this, and whether other car companies have done this as well. (All companies do variable tuning, and it’s “normal” to have modestly higher emissions in real driving compared to the test, but this was beyond the pale.) The question everybody is asking is “What the hell were they thinking?”

That is indeed the question, because I think the central issue is why VW would do this. After all, having been caught, the cost is going to be immense, possibly even ruining one of the world’s great brands. Obviously they did not really consider that they might get caught.

Beyond that, they have seriously reduced the trust that customers and governments will place not just in VW, but in car makers in general, and in their software offerings in particular. VW will lose trust, but this will spread to all German carmakers and possibly all carmakers. This could result in reduced trust in the software in robocars.

What the hell were they thinking?

The motive is the key thing we want to understand. In the broad sense, they did it because they felt customers would like it, and that would lead to selling more cars. At a secondary level, it’s possible that those involved felt they would gain prestige (and compensation) if they pulled off the wizard’s trick of making a diesel car which was clean and also high performance, at a level that turns out to be impossible.  read more »

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Image: John Matthies/flickr

Most of you will have heard about the revelations that Volkswagen put software in their cars to deliberately cheat on emissions tests in the USA and possibly other places. It’s very bad for VW, but what are the implications for robocars?

A lot has been written about the Volkswagen emissions violations but here’s a short summary. All modern cars have computer controlled ignition systems, and these can be tuned for different levels of performance, fuel economy and emissions. Cars have to pass emission tests, so most cars have to tune their systems in ways that reduce other things (like engine performance and fuel economy) in order to reduce their pollution. Most cars attempt to detect the style of driving going on, and tune the engine differently for the best results in that situation.

VW went far beyond that. Apparently their system was designed to detect when it was in an ignitions test. In these tests, the car is on rollers in a garage, and it follows certain patterns. VW set their diesel cars to look for this, and tune the engine to produce emissions below the permitted numbers. When the car saw it was in more regular driving situations, it switched the tuning to modes that gave it better performance and better mileage but, in some cases, vastly worse pollution. A commonly reported number is that, in some modes, 40 times the California limit for Nitrogen Oxides could be emitted. NOx are a major smog component and bad for your lungs. Even over a wide range of driving, it was as high as 20 times the California limit (about five times the European limit.)

It has not been revealed just who at VW did this, and whether other car companies have done this as well. (All companies do variable tuning and it’s “normal” to have modestly higher emissions in real driving compared to the test, but this was beyond the pale. The question everybody is asking is “What the hell were they thinking?”

That is indeed the question, because I think the central issue is why VW would do this. After all, having been caught, the cost is going to be immense, possibly even ruining one of the world’s great brands. Obviously they did not really consider that they might get caught.

Beyond that, they have seriously reduced the trust that customers and governments will place not just in VW, but in car makers in general, and in their software offerings in particular. VW will lose trust, but this will spread to all German carmakers and possibly all carmakers. This could result in reduced trust in the software in robocars.

What the hell were they thinking?

The motive is the key thing we want to understand. In the broad sense, they did it because they felt customers would like it, and that would lead to selling more cars. At a secondary level, it’s possible that those involved felt they would gain prestige (and compensation) if they pulled off the wizard’s trick of making a diesel car which was clean and also high performance, at a level that turns out to be impossible.

Why would customers want this?

Well, one answer is that there is an underground car-modding culture that already does this. Lots of people wish to hack their cars’ systems to boost performance, with little concern about the increased pollution. “Chip Tuning” is not always illegal, but often does increase emissions. They believe the emissions legislation just gets in the way of them of having a fun car.

But many more customers want performance and would not want to pollute the air. VW gave them a different magic solution — a better performing car and the illusion that they were not polluting. It’s not surprising that people might buy that. Another subset of customers will be genuinely upset that they were lied to and ended up hurting the environment. (Some research suggests that a number of deaths can be attributed to this extra smog.)

Who decided to do this?

We all want to know who decided this. It seems really unlikely that a lone rogue engineer would do it — what’s in it for her or him? Ditto for Bosch, the parts supplier. But engineers would have had to collude with any managers who decided to do this, and I even wonder what incentive they were given? Promotion? Bonus? Glory for creating an impossibly good engine? How did the managers decide to trust the colluding engineers with a company-risking secret?

How many levels of management knew?

It needs somebody high enough up that they win big by doing this. That means somebody who gets serious levels of bonus if they sell more cars, or whatever else this did for VW. That’s usually not a low level manager; it’s probably a manager for a large part of the car line. And, of course, did the top management plan or know this? It boggles the mind that they might have been so stupid, but it’s possible.

It’s also that possible high management asked the engine systems programmers to do this without informing the middle managers in the chain, but how? It seems hard to believe that lots of people would have conspired in this and could have fooled so many people, convinced they would not be caught. Getting caught means huge penalties, the end of not just your job, but your career. Possible jail time. Could the CEO have been involved? The board?

My best guess is a high level manager (high enough to benefit from increased sales in all the vehicles with this engine) but perhaps not the C-levels, who were somehow able to develop incentives for a key programmer. But we’ll find out eventually, I suspect.

For robocars…

It’s not too surprising that companies might cheat to improve the bottom line, especially when they convince themselves they won’t get caught. Where does that leave the  robocar maker?

My prediction is that robocar vendors will end up self-insuring their vehicle fleets, at least while the software is driving. Conventional insurance in PAYD mode may apply to miles driven with a human at the wheel. The vendors or fleet operators may purchase reinsurance to cover major liabilities, but will do so with a very specific contract with the underwriter which won’t protect them in the event of actual fraud.

If they self-insure, they have zero interest in cheating on safety. If they don’t make a car safe enough, they will be responsible for the cost of every accident. There will be nobody to cheat but themselves, though the pain of injury that goes beyond what a court awards still needs to be considered. One reason for self-insurance is that you will actually feel safer getting into a car, knowing it is the vendor who stands to lose if it is not safe enough.

Of course, in the event of an accident, vendors will work as hard as possible to avoid liability, but this comes at a cost of its own.

Cheats are far more likely if they benefit customers and increase sales. Examples might be ways that cars can break traffic laws in order to get you to places faster. Cars might park (actually “stand”) where they should not. Already there are cars with a dial that lets the occupant/controller adjust the speed above the speed limit, and, in fact, these dials are necessary. There have been lots of recent discussion about other ways in which it is necessary to not strictly observe the law in order to drive well on US roads.

One can imagine a number of other tricks that are not specific to robocars. Cars might try to cheat you on the bill for a taxi ride (just as cab drivers are known to deliberately take bad routes to get more money sometimes.)

VW/Audi have had some decent robocar projects, and VW’s sponsorship of Stanford’s VAIL lab has provided a lot of that. Now we must downgrade VW as a vendor that customers will not trust. (There is some irony to that of course, since at this point, VW is probably the least likely company to cheat going forward.)

Would suppliers lie?

There may be more risk from suppliers of technology for robocars. Sensor manufacturers, for instance, may be untruthful about their abilities or, more likely, reliability. While the integrators will be inherently distrustful, as they will take the liability, one can see smaller vendors telling lies if they see it as the only way to get a big sale for their business.

While they would end up liable if caught, they might not have the resources to pay for that liability, and be more interested in making the big time in the hope of not being caught. This risk is why the car industry tends to only buy from huge suppliers known as “tier 1” companies. The smaller suppliers, in tiers 2 and 3, aren’t allowed to sell to the big auto OEMs, because big auto companies won’t bet a car line on a small company. Instead, the small companies have to partner with a tier 1 that takes on that responsibility — and of course a chunk of the profits.

On the plus side, robocar designs generally expect parts and sensors to all fail from time to time, and so a good car design plans for failure and negotiates these safely with the ability, at the very least, to safely pull off the road — another car will be on the way quickly.

However, most tools do not plan on how to deal with a sensor that might deliberately provide false information, other than in planning defence against computer intrusion, which might turn a component into a malicious and untrustworthy device. But people are thinking about this, which can give us some comfort in respect of fraud by a supplier.

Self-certification

This scandal will probably raise more questions about the popular (and still probably correct) approach of having vendors self-certify that they have attained functional safety goals for their systems. These are actually unrelated issues. VW was not self-certifying, it was going through a government certification process, and cheating on it. If anything it actually reduces trust in government certification approaches. However, in the public eye, the reduced trust in vendors will extend to everything they do, including self-certification.

Vendors (large, reputable ones, at least) have strong motives not to lie on self-certification, both because they are liable for the safety failures that are their fault, and because they will be extra liable with possible punitive damages if they deliberately lied.

I have a longer article with more debate on the issues around government regulation and certification of robocars.

This article originally appeared on robocars.com.

If you liked this article, you may also be interested in:

• “Anyone who focuses on tech alone hasn’t grasped how autonomous driving will change society”
• Tricking Lidar and robocars
• Robocar news roundup: Google doesn’t hit Delphi but does go to Austin; Vislab sold for $30M
• VW launches robot that collaborates with workers

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

]]> https://robohub.org/removing-steps-of-common-processes/ Thu, 27 Aug 2015 08:13:52 +0000 http://robohub.org/removing-steps-of-common-processes/

Professor Robert J. Flatt. Source: DFAB

Being able to control the moment when concrete turns from liquid to solid is crucial for digitally fabricated concrete structures. The timing of this process can be controlled by tuning the chemistry and adding small amounts of specific substances at just the right time. Robert J. Flatt, Professor of Building Materials at ETH Zurich, discusses this process and the innovations in concrete chemistry and digital fabrication he and his team are working on to reduce the environmental footprint of the most used building material in the world.

“Test the limits and break through (…) no rules for me (…) let it go!”, you used this song from the Disney film “Frozen” in a presentation on your research. How are you working to get rid of rules?
I’d rather say: We try to do things that, at first, seem unfeasible. Lets take the making of a cake as an analogy. In general you have dough, which is fluid. You pour it into a mould and then put it into the oven to harden. What we are working on is similar to a process that would extrude this dough and have it immediately shaped and cooked. You could say: We are trying to remove steps of common processes by forcing the material to behave differently.

“The key is to use the critical moment when the material transforms from liquid to solid.” What does this mean in practice?
We are working on what I call the “spices” of concrete. Added to a mixture in very small amounts, these additives have a huge impact on the material properties. I give you an example. The research project “Smart Dynamic Casting” (SDC), a collaboration with the ETH Chair of Architecture and Digital Fabrication, started with the question: Can you make complex shapes of concrete without any formwork? SDC is an answer to this challenge, in which the key is to be able to use the critical moment when the material transforms from liquid to solid; when you can shape the material, but it doesn’t collapse under its own weight.

SDC also has been your first collaboration in the field of digital fabrication, before joining the National Centre of Competence in Research (NCCR) Digital Fabrication. Where are the synergies between material sciences and digital fabrication?
Digital fabrication in concrete wouldn’t work without the manipulation of the material properties. You either would end up with a very inefficient process or the process would simply fail. On the other hand, robotic control opens new perspectives to surpass current state-of-the-art construction processes, particularly for more individualized structures. For me this interdependency of material design and robotic processes is the exciting part about this research field, and bringing our expertise to this collaboration is where we see our role within the NCCR Digital Fabrication.

“A big opportunity is to combine the manipulation of the material properties with the reduction of the environmental footprint.” What is the added value of these new fabrication processes and materials compared to traditional ways of building?
If you take SDC, the overall interest was to be more efficient in producing complex shapes. So the added value is about creativity and efficiency. Furthermore, by replacing traditional formwork with a single adjustable slip-form, waste can be reduced. However, in terms of the overall environmental impact I consider the elimination of the formwork to be of second order. A much bigger opportunity is to combine the manipulation of the material properties with the reduction of the environmental footprint of concrete. Accordingly, the development of more environmentally friendly types of concrete is one of our main research focuses and also one of our major long-term goals, of which we plan to feed the results into the NCCR Digital Fabrication.

5 to 8% of the man made CO2 emissions is effected by cement production. Why do you focus on concrete and not on a building material with less environmental impact?
Concrete is the most used building material in the world. It is used in larger quantities than all the other building materials added together [1]. There are basically no other materials available in the quantity that can compete with concrete in terms of performance, environmental impact and cost. This huge volume of concrete also means that: If you simply succeed in reducing the amount of cement used in concrete you have a huge multiplication factor. As an example: about 40% of Switzerland’s Kyoto Protocol objectives where reached by the cement industry. Part of this reduction is due to the fact, that less concrete was used, part of it due to improvements in production, and part due to changes in the nature of the cement being produced. That brings us back to the “spices”; these additives can be used to tune the material properties, but you also can use them to keep required values of some properties while changing the proportions of the materials you used. As an example; chocolate producers are now allowed to replace 5% of the cacao fat with vegetable oil, but of course they don’t want to change the taste. In our research we try to do the same, but our goal is not to replace 5%, but 50% of the material. To accomplish this we need to formulate very good spices for it to go unnoticed!

In your experience, what factors are required for a research innovation so that industry will take interest?
An innovation, of course, needs a market perspective. In this sense environmental aspects are certainly a macro trend that impacts their long-term strategic considerations, however it is clearly the costs of materials, energy, and the impact of CO2 emissions that will influence marketability in the long term. The balances between impact issues and how to bring an innovation to market are definitively the high-level strategic considerations for industry.

So, if the NCCR Digital Fabrication wants to be successful, in practice it should focus on environmental issues?
This conclusion is too limited and brief, whereas the goals of the NCCR Digital Fabrication are long-term. I would rather describe the process as such: In the first phase we are more in the logic of developing something like a Formula One car, a niche product. So, of course we are concerned with doing things in a sustainable way, but we are still addressing a small portion of the market. We are looking at opportunities with high added value, rather than large volumes where processes are much more optimized and margins are very tight. At this stage looking at the large volume market from the perspective of digital fabrication could be a killer for innovation. Then, in a later stage, we intend to evaluate which part of our innovations can be adapted to larger scale use. This is where we can optimally shift our attentions to larger issues such as sustainability. Once we have resolved the smaller scale problems we can shift to volumes that allow us to have a large-scale ambition and a large-scale impact to improve sustainability.

Are there any risks you can think of regarding the path on which this NCCR is heading?
If you want to build a Formula One car and you can build it more efficiently with a robot that has special features, you might well be persuaded to also use this very versatile robot for normal serial production, but this may not be the most optimal solution. The big question for me is: Will our increased use of digital fabrication eventually lead to automation with a loss of design individualization? This is, of course, exactly the opposite of what we are aiming to accomplish within the NCCR Digital Fabrication. So, to answer your question, I think it is our mandate to bring affordable “mass customization” into construction and to use our research to ensure that individualization of design and construction is available for everyone.

[1] Yearly volumes: concrete 10 km3, fired clay 2 km3, timber 1.3 km3, steel 0.1 km3.

On this subject see also the newspaper contribution “Gewürze für mehr Nachhaltigkeit” of 25.06.2015 in “Tages-Anzeiger” (in German only).

]]> https://robohub.org/robocar-news-roundup-google-doesnt-hit-delphi-but-does-go-to-austin-vislab-sold-for-30m/ Mon, 13 Jul 2015 18:21:49 +0000 http://robohub.org/robocar-news-roundup-google-doesnt-hit-delphi-but-does-go-to-austin-vislab-sold-for-30m/ The press were all a-twitter about a report from Reuters that there had been a near miss between Delphi’s test car and one of Google’s though it was quickly denied that anything happened

The situation described, one car cutting off another, was a very unlikely one for several reasons:

• All these cars are operated by trained safety drivers who are expected to be vigilant and take control at any sign of trouble.
• In particular, special moves like a lane change would get extra vigilance. If something unusual happened (such as 2 cars going for the same spot) the safety drivers would be watching in advance, tracking what the car was doing, and pull back if the car’s own displays were not telling them it was going to do the right thing.

The safety drivers are not perfect of course, but an autonomous lane change is a rare event and one that most people are still just testing, so they would be very unlikely to miss that the car was going to cut somebody else off.

Of course, situations will arise when two cars try to change into the same spot at the same time, and robocars will probably be fairly timid in these situations. The most likely situation if two robocars tried to take the same spot would be that both would back off and return to their original lane, and it will probably be that way until being so timid is not a workable strategy.

Robocars won’t be the lane-changing demons that some people (including myself sometimes are.) Many human drivers are constantly trying to find the fastest lane and we weave, often finding the lane we move into seems to become the slowest. Part of that is our psychology.

Robocars won’t do this as much because their passengers will be occupied doing other things, and in most cases will not be in a super hurry. Those passengers will prefer a stable ride where they can get work done to a weaving ride with extra starts and stops. If we’re in a big hurry, we might ask the car to try to work extra hard to make the fastest trip but this will be the exception.

When we do want that, the robocar will actually have a very nice model of just how fast each lane is moving. It won’t be fooled the way we are by seeing some lanes that seem to be faster when in fact neither lane is winning by that much. If they read licence plates to identify cars, they will get excellent appraisals of what’s going on. If one lane is truly faster they will find it. On the other hand, they will be worse at the standard game of chicken needed to change lanes in heavy traffic, where you depend on the car you are moving in front of to slow down. They will know the physics though, and if a lane change is needed, they will warn the passengers of high acceleration and perfectly make a smaller spot than you might be able to make.

In other news, Google has sent two cars to Austin, Texas to expand their testing ground. I don’t have a particular insight on why they selected Austin — I know that many towns and states regularly contact Google in the hope they might bring some cars to their area, though Texas has no modified laws yet.

Vislab

I’ve written a few times about the work of Vislab in Parma, Italy. They have a focus on doing self-driving with machine vision, and did a famous cross-continent trek from Italy to Shanghai a few years ago, using a lead car to map the way and a following car self-driving, mostly with vision.

This lab was spun out of its university but now has been [acquired by Ambarella], a company that specializes in video compression chips. One can see why Ambarella would want a computer vision lab — but it seems this might spell the end of their self-driving efforts, unless they are spun out.

Emissions

A new paper is out in Nature Climate Change on the potential for robocars to reduce emissions, in spired by some of my research in this area. Sadly, it’s behind a paywall, but the author will give a talk at Nissan’s lab in Silicon Valley on July 15th at our local self-driving car meetup.

]]>

Google’s self driving car. Source: Google

The press were all a-twitter about a report from Reuters that there had been a near miss between Delphi’s test car and one of Google’s, though it was quickly denied that anything happened.

The situation that was described — one car cutting off another — was a very unlikely one for several reasons:

• All these cars are operated by trained safety drivers who are expected to be vigilant and take control at any sign of trouble.
• In particular, special moves like a lane change would get extra vigilance. If something unusual happened (such as two cars going for the same spot) the safety drivers would be watching in advance, tracking what the car was doing, and pulling back if the car’s own displays were not telling them it was going to do the right thing.

The safety drivers are not perfect of course, but an autonomous lane change is a rare event and one that most people are still just testing, so they would be very unlikely to miss that the car was going to cut somebody else off.

Of course, situations will arise when two cars try to change into the same spot at the same time, and robocars will probably be fairly timid in these situations. The most likely situation if two robocars tried to take the same spot would be that both would back off and return to their original lane, and it will probably be that way until being so timid is not a workable strategy.

Robocars won’t be the lane-changing demons that some people (including myself) sometimes are. Many human drivers are constantly trying to find the fastest lane and we weave, only to find that the lane we just moved into has become the slowest. Part of that is our psychology.

Robocars won’t do this as much because their passengers will be occupied doing other things, and in most cases will not be in a super hurry. Those passengers will prefer a stable ride, where they can get work done, to a weaving ride with extra starts and stops. If we’re in a big hurry, we might ask the car to try to work extra hard to make the fastest trip but this will be the exception.

When we do want that, the robocar will actually have a very nice model of just how fast each lane is moving. It won’t be fooled the way we are by seeing some lanes that seem to be faster when in fact neither lane is winning by that much. If they read licence plates to identify cars, they will get excellent appraisals of what’s going on. If one lane is truly faster they will find it. On the other hand, they will be worse at the standard game of chicken needed to change lanes in heavy traffic, where you depend on the car you are moving in front of to slow down. They will know the physics though, and if a lane change is needed, they will warn the passengers of high acceleration and perfectly make a smaller spot than you might be able to make.

In other news, Google has sent two cars to Austin, Texas to expand their testing ground. I don’t have a particular insight on why they selected Austin — but I know that many towns and states regularly contact Google in the hope they might bring some cars to their area, though Texas has no modified laws yet.

Vislab

I’ve written a few times about the work of Vislab in Parma, Italy. They have a focus on doing self-driving with machine vision, and did a famous cross-continent trek from Italy to Shanghai a few years ago, using a lead car to map the way and a following car self-driving, mostly with vision.

This lab was spun out of its university but now has been acquired by Ambarella, a company that specializes in video compression chips, for $30M. One can see why Ambarella would want a computer vision lab — but it seems this might spell the end of their self-driving efforts, unless they are spun out.

Emissions

A new paper is out in Nature Climate Change on the potential for robocars to reduce emissions, in spired by some of my research in this area. Sadly, it’s behind a paywall, but the author will give a talk at Nissan’s lab in Silicon Valley on July 15th at our local self-driving car meetup.

]]> https://robohub.org/the-year-of-cocoro-video-2452-jeff-robots-explore/ Fri, 19 Jun 2015 14:41:33 +0000 http://robohub.org/the-year-of-cocoro-video-2452-jeff-robots-explore/ The EU-funded Collective Cognitive Robotics (CoCoRo) project has built a swarm of 41 autonomous underwater vehicles (AUVs) that show collective cognition. Throughout 2015 – The Year of CoCoRo – we will be uploading a new weekly video detailing the latest stage in its development. This video shows autonomous Jeff robots as they explore a complex debris field.

The important issue here is the area coverage that can be achieved by the autonomous motion behavior. We found that a simple program called “correlated random walk with obstacle avoidance” does the job quite well. This program is straight forward motion altered by infrequent randomly triggered random turns and collision avoidance based on blue-light emissions and reflection at the nose of the robot. One robot covers the habitat quickly, and more robots do it even faster. This scalability is important to generate a useful robot swarm.

]]> https://robohub.org/self-driving-car-test-sites/ https://robohub.org/self-driving-car-test-sites/#respond Wed, 08 Oct 2014 19:06:00 +0000 http://robohub.org/self-driving-car-test-sites/

Swarm communication and urban city driving are integral to the safe deployment of self-driving cars. Mercedes-Benz and a joint Michigan-based consortium are setting up secure test sites in California and Michigan to test their solutions.

Mercedes-Benz, along with local governments, is turning what used to be the Concord Naval Weapons Station into the US’s largest secure testing site for self-driving vehicles and new transportation technology testing. The facility will use the nearly 20 miles of existing paved roadways to test autonomous vehicles as well as communication technologies between cars and traffic signals.

In Ann Arbor, Michigan, a mock-up of busy streets, complex intersections, confusing lane markings and construction crews will be used to gauge the latest automotive sensors, algorithms, and other technologies. The site will consist of four miles of roads and 13 different intersections. A spokesman for the University of Michigan’s Mobility Transformation Center, which is overseeing the project, said: “Having identified challenging scenarios, we need to re-create them in a highly repeatable way. We don’t want to be just driving around the public roads.”

“I think it’s a great idea,” says MIT Professor John Leonard. “It is important for us to try to collect statistically meaningful data about the performance of self-driving cars. Repeated operations — even in a small-scale environment — can yield valuable data sets for testing and evaluating new algorithms.”

“[Driverless car] technology could provide solutions to some of our most intractable social problems — the high cost of traffic crashes and transportation infrastructure, the millions of hours wasted in traffic jams, and the wasted urban space given over to parking lots, just to name a few. Driverless cars have the potential to fundamentally alter transportation systems by averting deadly crashes, providing critical mobility to the elderly and disabled, increasing road capacity, saving fuel, and lowering emissions.” Quote from KPMG Issues and Insights article.

Analysts predict $1.3 trillion in savings in the United States and $5.6 trillion globally, from the deployment of driverless cars over the next three decades.

]]> https://robohub.org/self-driving-car-test-sites/feed/ 0 https://robohub.org/air-water-energy-and-food-in-a-nutshell-space-exploration-as-driver-for-sustainable-robotic-agriculture/ Mon, 04 Nov 2013 05:54:11 +0000 http://robohub.org/?p=22125

University of Colorado’s robotic plant growth is demonstrated at the Kennedy Space Center. Source: NASA.

Targeting a sustainable presence of humans in outer space will require solving air, water, energy, and food supplies within a few thousand cubic feet surrounded by vacuum. What seems at first sight to be a problem of an apocalyptic, remote future reveals itself as the grand challenges of our civilization in a nutshell. This article argues that space exploration can be one of the main drivers to revolutionize sustainable agriculture on earth.

First, the agricultural industry has classically not been the driver, but on the receiving end of innovation in automation. Current economic drivers promote increasing the size of farm equipment and mono-cultures, which are more suitable to automation. Thinking about solving food production on a space-ship, Mars-colony or city-scale, which have opposite requirements than industrial agriculture, makes it clear that solutions will not come from incremental changes to the current system, but require a disruptive approach that has very little to do with current agricultural practice. Second, sustainable agriculture is a systems challenge that does not stop at innovation in automation, but also requires advances in renewable energies and integration into water and air management to be successful, in particular when considering integration of agricultural production into urban environments. Third, advanced life support systems are not only mission-critical for long-term exploration missions, but the National Aeronautics and Space Administration’s (NASA) support strongly hinges on the perceived value of its mission; using space exploration as a driver to solve our most pressing grand challenges is a strong narrative to gain public support.

A brief history of agriculture

Since the advent of agriculture around 12,000 years ago, humans have developed a highly sophisticated system for global food production with the most rapid technological advances occurring during the first half of last century. In the 1920s, agriculture had not only adopted new machinery, but also the financial, cultural, and ideological apparatus of industrialism. This process has led to farm equipment of ever-increasing size, modern plant breeding programs, the use of synthetic fertilizers, delivery of water via irrigation systems, and the use of pesticides to control crop herbivory, which have all contributed to a tremendous increases in crop yield. For example, corn yields in the US increased approximately 400%-500% from 1940 to 1997. Together with consolidation of small farms into larger ones, the number of people that a single farmer in the US provides for increased 9-fold from 15.5 people per farm in 1950 to 140 people per farm in 1997.

While providing immense cultural benefits, these developments came at tremendous environmental costs. Increased fertilization has led to excess nitrogen and phosphorus in the water systems impacting both human health and the integrity of aquatic ecosystem, and also to increases in nitrous oxide production (a potent greenhouse gas). More recently, there is also an increasing awareness that the global supply of phosphorus, which is a non-renewable resource but an essential plant nutrient contained in most synthetic fertilizers, is expected to peak mid-century and decline thereafter.  Also, cultivation of just a few crops (corn, soybeans, hay and wheat make up 68% of farm land in the US) in ever-increasing monocultures and the resulting lack of plant diversity make these systems vulnerable to large-scale pest outbreaks. Finally, the high specialization on certain crops in different parts of the US – which is the result of industrial streamlining the process – requires considerable transportation cost, and might become infeasible with increasing cost of oil.

Taken together, there is a critical need to develop agricultural practices that deliver water and nutrients in a manner that minimizes losses from these systems, while creating an ecologically resilient agricultural system that can withstand or quickly recover from disturbances such as pest outbreaks, for example by using companion plants and poly-cultures.

Figure 1: Artist impression of an indoor precision agriculture system that is co-located with people. Artwork by Nick Dragotta.

Advances in robotics can decrease detrimental effects of farming by precise administration of water and nutrients and inter-cropping, while bringing agriculture closer to consumers. Besides being able to provide individual plants with the required resources on an as-need basis, small-scale robotic platforms are not limited to operating on fields, but could also reclaim urban environments that are currently deprived from agriculture and horticulture, such as within offices, shopping malls or on roofs. A concept drawing of a team of robots cultivating plants in a shopping mall is shown in Figure 1.

It is worth noting that neither agriculture nor horticulture have ever been the main drivers for innovation in automation. Rather, industrial methods and techniques were adapted to agriculture long after they have proven successful in other trades. This trend seems to be persistent still today. For example, automation in agriculture is enabled exclusively by the availability of small-scale and cheap computation, which has been driven by the electronic spread-sheet. Similarly, disruptive actuation and sensing technologies that have the potential to bring agricultural automation to a new level are being developed in orthogonal markets, such as the gaming industry, manufacturing, or construction.

Indeed, major industrial players in precision agriculture support their technical innovations by developing for the construction industry, e.g., large earth moving equipment, which provides higher margins than agriculture or horticulture. Based on this history and lack of economical drivers that will require industry to leap from large-scale automation to urban-scale precision agriculture, I argue that truly disruptive innovation is more likely to be developed for niche applications, such as space exploration.

Air, water, energy and food in a nutshell
Going to Mars is in the tradition of setting foot on the moon, exploring the West, and ultimately the very exploration that led to the discovery of America. All these missions have in common that they are variants of the “knapsack problem”. Explorers need to decide on a combination of provisions and tools that allow them to maximize exploration and minimize risk of failure. Parameters of this problem are the set of brought-along goods, available resources harvested on the way, and the constraints of vessel size. Larger vessels allow more goods to be brought along, but also require larger crews to maintain them, again requiring more resources.

A space mission adds an additional complication as the launch mass is limited by the amount of fuel. The larger the rocket, the more fuel is needed, in turn requiring more propulsion to increase launch mass. This optimization problem currently limits how long we can sustain ourselves in space and therefore where we can go and what we can do there. While advances in agricultural practices and transportation systems have solved this problem for humans who have now permanently settled earth’s most remote spots, this approach is about to reach its limitations on earth and does not extend to space.

Considering the vast emptiness of space (and the scarcity of resources on other planets), solutions to this problem will require us to make better use of resources found in place, and to think about how to recycle them. For example, food can be grown and fertilized from “black water” and help to turn toxic carbon dioxide into carbon – to remain in the plant – and oxygen. While maintaining a fully enclosed ecosystem that is significantly smaller than our own planet and can support human beings has not been accomplished yet, doing the math on launch mass and potential yield has shown that growing food in space becomes advantageous for missions exceeding two years in space. For missions shorter than that, the additional launch mass and space of the tools and provisions that plants require is better used by bringing additional resources. An alternative scenario is to launch life support systems to arrive before humans do (Figure 2). In both cases, automation is necessary as the use of humans to perform these tasks is highly inefficient in a space scenario.

A major payload driver for autonomous food production is the additional required water resources. Yet, after reaching a critical mass, plants are an excellent natural system for converting black water into drinking water. Hereby, plants consume the water via their roots and return purified water into the local atmosphere via evaporation. Although small-scale systems to replace waste-water treatment plants in remote areas have been successfully demonstrated, additional research is needed to implement such systems in a self-contained, easy to maintain, fashion. Future long-term space exploration missions are likely to depend on a combination of bio-chemical processing and biological filtration, requiring a systems view and increased understanding of the micro-biology of the underlying processes. Although other planets provide massive reservoirs of frozen water in their pole caps and under their surface, water shortage has become a major problem in the US west of the continental divide and large areas of the world are subject to desertification, making water shortage a global problem, and requiring drastic increase and decentralization of processing. While water shortage for now mainly affects our quality of life, water conflicts have been linked to the Rwandan genocide and the war in Sudanese Darfur.

Figure 2: Habitat design that can be pre-deployed on Mars and will significantly extend air, water, and food resources due to an integrated approach of waste water reclamation and air purification. (From Bioregenerative Life Support System (BLSS) for Long Duration Human Space Missions.)

Plants also have the capability to absorb carbon from the air and releasing oxygen. On earth, this task is to a large part accomplished by tropical rain forests, which are responsible for roughly a third of the earth’s oxygen turnover. For space exploration, plants alone are not sufficient, requiring machines to scrub carbon dioxide from the atmosphere. While regenerative carbon dioxide scrubbers – a process mainly requiring electricity – have been in use on the now decommissioned space shuttle, terrestrial applications include carbon dioxide reduction of power plant exhausts. Albeit feasible, current technology is not cost-efficient to deploy and to operate, mainly due to the lack of economical drivers. This research would be desirable, however, as carbon dioxide emissions are believed to be the main driver behind man-made global warming, with its long-term effects yet to come.

Lighting for food production and photosynthesis, water purification, and carbon dioxide scrubbing will require additional energy, further driving the required launch mass of an exploration vessel or station equipment. Energy is available in effectively unlimited quantities from the sun, but requires efficient conversion. On earth, solar power is also an attractive alternative energy source for earth-based applications and could drastically reduce our dependency of fossil fuels, which are both a source of international conflicts and carbon dioxide emissions. Current solar cell technology is not yet competitive with electricity generated from fossil fuels and nuclear power, requiring additional research into reducing production cost while enhancing efficiency. A space mission could be a significant driver for the latter without being limited by the economical drivers of fossil fuels that dominate next-generation solar cells that industry deems economically viable.

 

Space exploration as a driver for our most pressing grand challenges
Space exploration has historically been a geo-political, strategic instrument. Showing the ability to precisely place an object into lower earth orbit or onto the moon demonstrates the capability to project power at long distance with high accuracy. In addition to leading to game-changing military capabilities, space exploration has transformed life on earth. Sputnik, the first radio satellite, led the way to worldwide telecommunication and global positioning. Sputnik also spurred a space race, leading to launch systems of increasing size and precision, eventually culminating into the Apollo program, the first human on the moon and the strategic defense initiative (SDI), also known as “Star Wars”. Albeit the collateral science and engineering benefits of these missions are beyond doubt, they became increasingly less tangible.

NASA has recovered from this by focusing its missions on atmospheric sensing, revolutionizing the fields of geology, agriculture, archeology and many others, and space exploration leading to jaw-dropping and deeply inspiring photographs of outer space that have fundamentally changed our understanding of the universe and our role therein. Nevertheless, the cost of these missions seems to less and less justify their benefits.  With the industrialized nations accumulating prodigious amounts of debt and the developing countries fighting over water and food, understanding the origins of our universe and setting foot on other worlds becomes more and more a secondary goal in public perception.

NASA is currently rallying interest for a “planetary defense” mission with the goal of robotically bringing asteroids into a near-earth orbit where they can be used as a shield to deflect asteroids such as the one grounded in Russia in the spring of 2013. Albeit such a mission supports the geo-political narrative of the US as global guardian and would lay the technical foundation for a paradigm shift from earth-launched to space-launched exploration, the actual risk of an apocalyptic asteroid impact is minuscule compared to risks arising from political instability and resource problems elsewhere in the world.  Therefore, it is unlikely that such a mission can inspire the same national energy that the space race did, and which is imperative for the success of a manned mission to Mars.

Instead of motivating space exploration with geopolitical advantages and science outcomes that are inaccessible, or even moot, to the general public, I argue to identify missions whose success is aligned to solve mankind’s greatest challenges: food, energy, water and air.

Next steps in robotic research

Figure 3: Remote-operated greenhouse with self-contained light and water supply (left).

With growing food in space not on the critical path of missions immediately ahead, but a long-term requirement, research in space-based agriculture should focus on the following three fronts: increasing our knowledge of in-space plant growth, solving the key perception and manipulation challenges of plant maintenance, and understanding the impact that observing, maintaining and eating plants has on humans in the isolation of space. These three thrusts are closely inter-related and can benefit from automation. Indeed, plant growth experiments are recurrently undertaken on the ISS and could tremendously benefit from automation. For example, light-weight, low-energy robotic arms could enable scientist to systematically sense within the plants’ canopy, and automated management of air, water, and nutrients on a per-plant basis would allow us to better understand how the space environment affects these parameters.

As fully autonomous plant maintenance requires solutions to a series of hard problems in perception and manipulation, initial focus should be on remote operation of the growing process (Figure 3, left). Devising a system that solves all the mechanical, user interface and communication challenges that would allow to grow plants (from seeding to harvest and re-planting) can serve as the basis for further developing automation and could motivate its own mission such as deploying a greenhouse container to Moon or Mars.

Figure 4: The “Data Garden”, a gantry system to collect the data basis for autonomous plant operations (left). 3D point clouds, which can be the basis for remote-operation planning (right).

Concerning human-factors, there is strong evidence that humans living in the isolation of space will drastically benefit from interactions, including taking care of, harvesting and eating, of plants. Active research challenges here are how to design this experience to be most beneficial for the astronauts. This includes not only identifying care-taking tasks that the astronauts actually enjoy, but also providing solutions to automating those tasks that are undesirable or induce additional stress. In the long run, remote operation will be more and more subsumed by actual autonomy. Here, key challenges are automatic assessment of plant status, manipulation of soft, flexible objects, and dealing with adverse environmental conditions such as mud, water and unpredictable growth that can quickly jeopardize a running system.

Summary
Our agricultural system is about to reach its limitations, with demand for its products to outpace availability of resources. Space exploration is concerned with similar challenges, albeit at an extreme scale: water, energy, and air need to be turned into food in a nutshell in a most sustainable way that minimizes the influx of external resources. While industrial agriculture addresses its challenges by ever-increasing monocultures that are economical to automate, the needs of future urban centers on earth and colonies in outer space require an opposite approach: small-scale precision agriculture that provides care to plants on an as-need basis and that can integrate with water purification and air revitalization needs of its consumers. As the technological leap this approach requires is gigantic, it is unlikely to be performed by the agricultural industry, whose economics exclusively support incremental changes. This is not the case for space exploration, which can – given strong public support of its mission – support disruptive technological advances such as sending a man to the moon and eventually allow us for sustainable existence on other planets. This is a challenge that dwarfs sustainable living on earth.

]]> https://robohub.org/little-known-uses-for-robots/ Sat, 14 Sep 2013 18:53:00 +0000 http://robohub.org/?guid=a8b798922735a8b2dcd380461fe0b4e8 Five little known uses for robots: (1) explosives handling by explosives manufacturers and also by armed forces that must dispose or handle them; (2) using lasers on robotic arms to strip paint from air force plans; (3) having a robot scale the heights of a dam or nuclear chimney to inspect and analyze the concrete; (4) securely store valuable vehicles in vaults or robotically park cars in special car parks, and (5), wacky art. See photos and videos.

Explosives Handling

Source: Dreamstime Stock Photos.

A Chinese firm specializing in explosives manufacturing has decided to upgrade over 100 installations with parallel handling robots from Adept Technology. In a similar vein, iRobot just won a $30 million contract from the U.S. Army for robotic systems to be used for bomb disposal and other dangerous handling missions by troops and first responders.

Paint Stripping

Rendering of robots lasering paint removal from plane. Source: CTC.

Paint stripping of air force jets by robot arms gripping lasers. “Automated laser de-coating is expected to significantly reduce labor, waste, environmental risk and overall cost,” said the project manager of a joint effort between CMU’s NREC, the US Air Force and CTC. The laser coating remover uses a continuous wave laser to strip paint and other coatings; it replaces the traditional abrasives or chemical paint removers which generate significant hazardous wastes and air emissions.

Concrete Checking

Click to see EPRI and NY Power Authority video of robot crawler climbing dam face with echo sounding sensor. Source: EPRI

A new crawler robot developed by the EPRI (Electric Power Industry Institute) climbs up vertical surfaces and inspects, analyzes, cleans and paints. The robot is perfect for places with difficult accessibility like the face and walls of a large dam or particularly hazardous places like nuclear facilities.

Vehicle Vault and Robotic Parking

Source: RoboVault brochure.

Vehicle vaults for secure storage of valuable vehicles and robot parking systems: the RoboVault system accepts and then transports the vehicle to a controlled storage area. When it is time to retrieve the vehicle, the process is repeated in reverse. Robotic Parking Systems has robotic parking installations from Florida to Dubai, and from Abu Dhabi to Hoboken, NJ.

Just Plain Wacky

A Brooklyn-based robot artist uses his creatures for various purposes. His latest production is as a choir and musician for a performance in a church. Chico MacMurtrie is his name and his website is Amorphic Robot Works. The NY Times did an in-depth story with lots of pics. A 2012 youTube video about the artist’s New Year’s Eve party suggests how it might sound.

]]> https://robohub.org/ted-global-2013-speaker-lian-pin-koh-on-conservation-drones/ Tue, 11 Jun 2013 19:17:27 +0000 http://robohub.org/?p=15194

Lian Pin Koh (left) and Serge Wich (right) in Zurich with an early prototype of Conservation Drone.

TED Global speaker/drone ecologist Lian Pin Koh and fellow researcher Serge Wich share how drones are playing an important role in helping conservationists survey and map ecologically sensitive parts of the globe.

Global land-use changes continue to be a major driver of biodiversity loss and greenhouse gas emissions. Remote sensing technology is increasingly used to assess changes in land use, species distributions and carbon stocks. However, satellite and airborne sensors can be prohibitively costly and inaccessible for researchers, or they may not have the required spatial resolution. Recently UAVs have been used by conservation researchers and practitioners across various parts of the world. These inexpensive UAVs typically cost less than $4000 US, and have been dubbed ‘Conservation Drones’. The drones are equipped with cameras to record videos at up to 1080 pixel resolution (high definition), and acquire aerial photographs of <2 cm pixel resolution. Aerial photographs can be stitched together to produce near real-time geo-referenced land use/cover maps of surveyed areas and 3D models.

This post is part of Robohub’s TED Global 2013 coverage.

Serge Wich and Lian Pin Koh preparing a Conservation Drone for a demonstration mission for the French conservation group, HUTAN, near the Kinabatangan river in Borneo.

Why did we develop Conservation Drones?
Globally, biodiversity continues to decline, and a disproportional amount of this decline occurs in the tropics where the majority of global biodiversity is found. One urgent challenge for conservationists is to be able to accurately assess and monitor changes in forest cover, species distributions and population dynamics. To obtain such data, conservationists currently rely on satellite-based remote sensing for mapping and monitoring land use changes, and on ground surveys to determine and monitor species distribution and population dynamics. Although low-resolution satellite images are freely available at specific time intervals, it is often prohibitively expensive to obtain sub-meter resolution images. Yet, such high-resolution data are often critical for accurately detecting and tracking land use change at the landscape scale. Furthermore, large portions of the humid tropics are often obscured from remote sensing satellites due to persistent cloud cover. As such, cloud-free satellite images for a specific time period/series and location are often not readily available.

An elephant detected during one of the drone missions in North Sumatra, Indonesia.

A second major conservation challenge concerns assessment and monitoring of biodiversity. Currently, this is largely achieved through ground surveys, which are often time-consuming, financially expensive, and logistically challenging in remote areas. As a result, surveys are not conducted at the frequency required to monitor population trends, and some remote tropical forests have never been surveyed for biodiversity due to difficult and inaccessible terrain.

An additional challenge for conservationists is the illegal encroachment into protected areas and illegal hunting of prized animals, such as tiger, rhinos, and elephants. The areas that need to be surveyed in these cases are large, and current ground and manned aircraft surveys do not occur regularly enough to be able to effectively reduce illegal activities.

To address these challenges, we are developing the use of inexpensive, autonomous unmanned aerial vehicles for surveying and mapping forests, biodiversity and potential illegal activities – Conservation Drones.

Drone image of a forest in Cambodia.

What are Conservation Drones?
Although we have been using several airframes for our drones since we started, the core part of the system has remained the same. The core is an autopilot system (APM) developed by an online community (diydrones.com). By combining the APM with open-source mission planner software (APM Planner), we convert off-the-shelf model airplanes into drones. We use inexpensive airframes so that the technology can be accessible to conservation organizations and researchers, who often do not have the funding to acquire drones and maintain them.

The sensors
We have equipped our drones with various camera systems for still-photography and videography. We have been mainly using the Canon SX230 with a build-in GPS so that all photos are geo-tagged. We replace the original firmware of the Canon camera with a Canon Hack Development Kit. This ‘hacked’ firmware allows us to implement a customized intervalometer script to command the camera to take photographs at user-specified time intervals (e.g., every 3 seconds). This script also allows the user to define several other parameters including: i) time-delay before the camera begins taking pictures, ii) focal length of camera lens, and iii) time before camera automatically shuts down and retracts its lens.

We also use video cameras such as the GoPro Hero and the ContourGPS. These take high definition videos at 1080 x 720 pixels. We attached these cameras underneath or on the side of the fuselage. Using the APM Planner, we program the flight path of each mission by clicking on waypoints in a Google satellite map interface. The drone can be programmed to take off and land autonomously, and circle over any waypoint for a specified number of turns or duration. Users could also program other flight parameters such as ground speed and altitude of each waypoint.

A mosaic of drone images during a mission over an agricultural landscape in Sabah.

What have we achieved so far?
Since our start in January of this year we have made over 200 conservation drone flights in several countries including Switzerland, Netherlands, Indonesia, Malaysia and Nepal, Congo, Gabon, Madagascar, United States, and Greenland. These flights have provided us a large amount of photos and videos, which we have examined with respect to our three main initial goals. We describe these below.

Mapping land use
So far we have been able to take sets of high-resolution photos of various areas that can be stitched together into a geo-referenced mosaic so that it can be used in geographic information system software. Such mosaics give detailed information on type of land use, agriculture, and settlements. In addition, the images can be used to create three-dimensional models of the areas that were covered during missions due to the overlap between the photos. Such models can potentially be used to calculate a number of characteristics of different land uses such as tree height and tree density.

Biodiversity
The high-resolution nature of our images have also allowed us to detect various wildlife species on our photos or their signs including orangutans and their nests, elephants, rhinos, forest buffaloes, and even turtle nests. The next important step for our work is to derive the distribution and density of these wildlife species based on drone images so that this technique can become a standard application for conservation workers. To achieve this goal, we are collaborating with colleagues, including Prof. Dr. Andreas Krause at ETH Zurich to automate the detection of orangutan nests.

Illegal activities
For conservation workers, having access to up-to-date information on illegal logging in protected areas and poaching are extremely important. The video and photos taken from the drones can be used to detect such these illegal activities. For example, geo-tagged drone images of recently logged areas could help authorities track down illegal loggers and provide evidence for their conviction. When poachers are in a forest, they often create campfires for cooking or smoking the bush-meat from animals they have hunted. The detection of smoke rising above a forest would thus be very useful to locate these poachers. Conservation drones equipped with a high definition video camera could facilitate the detection of smoke many kilometers away. Furthermore, a ‘live’ video link would allow rangers to patrol the forest in real time, and react immediately when needed.

Drone images of orang-utan nests acquired during missions in Southeast Asia.

Plans for the future
Conservation Drones is a constant work in progress. We are currently working with other colleagues to explore the use of our drones as a ‘data mule’. For example, drones equipped with a scanning radio receiver might be able to triangulate the location of forest animals that have been tagged with a radio collar. This would be a much more efficient way of locating these radio-collared animals than the traditional method of walking the forest on foot with a cumbersome radio antenna.

We are also working with WWF Nepal and India to equip drones with thermal imaging cameras. These camera systems would be able to detect heat emitting objects from the ground, which would help rangers locate both wildlife and poachers at night.

 

Further Reading
Koh, L. H., Wich, S. A. (2012) Dawn of drone ecology: low-cost autonomous aerial vehicles for conservation. Tropical Conservation Science 5: 121-132.

www.conservationdrones.org

 

See all the posts in Robohub’s TED Global 2013 coverage.

]]> https://robohub.org/eight-robotic-innovations-among-2013-edison-award-winners/ Wed, 01 May 2013 22:56:42 +0000 http://robohub.org/?p=13474 Last Thursday in Chicago at a ceremony attended by 400 international business leaders and innovators, the Edison Awards – which honours game-changing new products and services – announced its 2013 winners. While the innovations featured at the event crossed a broad spectrum of industries and applications, seventeen of 130+ award-winners came from the fields of robotics, automation or sensing.

Here they are …

Baxter by Rethink Robotics (Gold Award – Productivity Tools)
Rethink Robotics creates robots for manufacturers that are different: Robots with Common Sense that anyone can use, just about any company can afford, and require no programming.

iRobot Looj® 330 Gutter Cleaning Robot (Gold Award – Household)
iRobot Looj 330 cleans up to a 30-foot section of gutter in 5 minutes and up to 200 linear feet per charge. The remote control has a communication range of up to 50′, allowing users to remain in a safe position while the robot cleans further. The low profile design allows Looj to fit in 90-percent gutters worldwide, traveling under gutter straps and over downspout holes.

Wave Glider® by Liquid Robotics (Gold Award – Power Generation/Utilization)
Many of the most dramatic challenges humanity will face in the next century will relate to our oceans. Liquid Robotics is revolutionizing the observation of our oceans with the invention of the Wave Glider, the 1st wave powered marine robot able to stay at sea for year without fuel/personnel/no emissions.

Quill by Narrative Science (Gold Award – Collaboration/Knowledge Management)
Quill is an engine that automatically transforms structured data into narratives indistinguishable from those generated by humans. A synthesis of data analytics and artificial intelligence, Quill generates English language briefs based on insights it derives from the data it processes. It finds and explains the insight hidden in your data.

ecoATM® by ecoATM, Inc. (Gold Award – Environment/Conservation)
ecoATM’s automated self-serve recycling kiosks use patented, advanced machine vision and artificial intelligence to evaluate and buy-back used electronics from consumers for cash. By providing convenience and immediate cash incentive, ecoATM’s kiosks are dramatically raising recycling rates and paying millions of dollars to consumers in the process.

Advanced Robotic Laser Coating Removal System (ARLCRS) by Carnegie Mellon University’s National Robotics Engineering Center and Concurrent Technologies Corporation (Gold Award – Processes)
The Advanced Robotic Laser Coating Removal System (ARLCRS) uses a powerful laser depainting tool and state-of-the-art mobile robots to automatically remove paint and coatings from aircraft. A custom HEPA system collects debris, minimizing its impact on the environment. The complete system is scalable from fighters to cargo and tanker aircraft.

MakerBot® Replicator® 2 Desktop 3D Printer by MakerBot (Gold Award – Design)
The MakerBot® Replicator 2 Desktop 3D Printer is the easiest, fastest, and most affordable tool for making professional-quality models. Designed for the desktop of an engineer, designer, or “maker,” the MakerBot Replicator 2 sets a new standard in 3D printing with 100-micron layer resolution and 410 cubic inch build volume.

Bioprinters for Regenerative Medicine by Wake Forest Baptist Medical Center’s Institute for Regenerative Medicine (Gold Award – Game Changer)
Two unique printers designed by scientists at the Wake Forest Institute for Regenerative Medicine print living cells and biomaterials rather than ink. The goal is to print replacement tissues and organs for human patients. Current projects include printing skin cells onto burn wounds and printing a prototype human kidney.

ARTAS® Robotic System by Restoration Robotics, Inc. (Gold Award – Aesthetics)
The ARTAS® System is a physician-controlled, state-of-the-art, interactive, computer-assisted system that enables harvesting of hair follicles during hair restoration procedures. ARTAS utilizes a robotic arm guided by special imaging technology to enhance the quality of hair follicle harvesting for the benefit of physicians and their patients.

Magellan Microprocessor Foot Ankle system by Orthocare Innovations (Gold Award – Assistive Devices)
Magellan recreates organic movement for people with lower limb prostheses. Magellan intuitively adjusts to the user’s movements, provides greater control, wider range of motion, more comfort and stability than other devices on the market. Magellan is the first prosthesis linking users with clinicians through mobile communications technology and cloud computing.

MatrixSelect Automated Storage and Fulfillment System by Symbotic LLC (Silver Award – Productivity Tools)
Symbotic’s MatrixSelect has developed an advanced analytic solution leveraging a hierarchical framework for optimal autonomous guidance of its mobile autonomous robots to transform how materials are sourced and distributed through warehouses delivering a higher ROI for high throughput, optimal space utilization and flexible configuration through an existing supply network.

Kingfisher Unmanned Surface Vessel by Clearpath Robotics (Silver Award – Research and Collaborative Tools)
The Kingfisher M200 is an unmanned surface vessel with applications ranging from environmental data collection to harbor safety. Collecting nearly 100 times more data, up to eight times faster than traditional survey methods, the Kingfisher can cut labor and budget requirements by 60% – all while dramatically improving onsite safety.

Hermes by Advanced Optical Systems, Inc. (Silver Award – Safety)
Flying over life-threatening IEDs, mines and roadside bombs is a critical goal of US military logistics. Advanced Optical Systems (AOS) has developed the Hermes proximity, location and ranging system, giving pilotless helicopters the ability to pick-up and deliver supplies autonomously. This revolutionary system is currently in Afghanistan.

Mixed Row Palletizing (MXRP) Gripper by Grenzebach Americas – RSW BV (Bronze Award – Productivity Tools)
KUKA Systems offers a new, innovative Mixed Case Row Palletizing (MXRP) cell that can deliver efficiency gains of 40% or more in building same-store pallets in the warehouse.

Guideline Robotic Convoy System by Autonomous Solutions, Inc. (Bronze Award – Safety)
Guideline Robotic Convoy System is a simple but revolutionary way to guide robotic convoys through combat zones, industrial sites, and other dangerous areas. The Guideline tether attaches to any leader, and algorithms measure the cable length and vector to calculate the exact course for the unmanned follower vehicle.

Intelligent Lighting System by Digital Lumens (Bronze Award – Lighting)
Digital Lumens is redefining industrial lighting with intelligent LED lighting systems and services that deliver unmatched energy savings, flexibility and unique value to customers. With smart, networked LED fixtures that are centrally managed via software, the Intelligent Lighting System is proven to deliver lighting energy savings of up to 90%.

mySentry Remote Glucose Monitor by Medtronic Diabetes (Bronze Award – Assistive Devices)
mySentry, the world’s first remote glucose monitor of an integrated insulin pump with Continuous Glucose Monitoring (CGM), was designed to enhance nighttime protection with sensor alerts and alarms that can awaken a caregiver of a person with diabetes to important information.

If you liked this article, you may also be interested in:

• iRobot, 3D Systems and Makerbot recognized at Economist’s 2013 Innovation Awards
• New ETF (NASDAQ:ROBO) focuses on robotics industry
• Startup Series #5: Rodney Brooks, Steve Cousins & Pioneers Festival

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