The National Science Foundation (NSF) announced a $6.1 million, five-year award to accelerate fundamental research on wireless communication and networking technologies through the foundation’s Platforms for Advanced Wireless Research (PAWR) program.

Through the PAWR Project Office (PPO), award recipients US Ignite, Inc. and Northeastern University will collaborate with NSF and industry partners to establish and oversee multiple city-scale testing platforms across the United States. The PPO will manage nearly $100 million in public and private investments over the next seven years.

“NSF is pleased to have the combined expertise from US Ignite, Inc. and Northeastern University leading the project office for our PAWR program,” said Jim Kurose, NSF assistant director for Computer and Information Science and Engineering. “The planned research platforms will provide an unprecedented opportunity to enable research in faster, smarter, more responsive, and more robust wireless communication, and move experimental research beyond the lab — with profound implications for science and society.”

Over the last decade, the use of wireless, internet-connected devices in the United States has nearly doubled. As the momentum of this exponential growth continues, the need for increased capacity to accommodate the corresponding internet traffic also grows. This surge in devices, including smartphones, connected tablets and wearable technology, places an unprecedented burden on conventional 4G LTE and public Wi-Fi networks, which may not be able to keep pace with the growing demand.

NSF established the PAWR program to foster use-inspired, fundamental research and development that will move beyond current 4G LTE and Wi-Fi capabilities and enable future advanced wireless networks. Through experimental research platforms that are at the scale of small cities and communities and designed by the U.S. academic and industry wireless research community, PAWR will explore robust new wireless devices, communication techniques, networks, systems and services that will revolutionize the nation’s wireless systems. These platforms aim to support fundamental research that will enhance broadband connectivity and sustain U.S. leadership and economic competitiveness in the telecommunications sector for many years to come.

“Leading the PAWR Project Office is a key component of US Ignite’s mission to help build the networking foundation for smart communities,” said William Wallace, executive director of US Ignite, Inc., a public-private partnership that aims to support ultra-high-speed, next-generation applications for public benefit. “This effort will help develop the advanced wireless networks needed to enable smart and connected communities to transform city services.”

Establishing the PPO with this initial award is the first step in launching a long-term, public-private partnership to support PAWR. Over the next seven years, PAWR will take shape through two multi-stage phases:

• Design and Development. The PPO will assume responsibility for soliciting and vetting proposals to identify the platforms for advanced wireless research and work closely with sub-awardee organizations to plan the design, development, deployment and initial operations of each platform.
• Deployment and Initial Operations. The PPO will establish and manage each platform and document best practices as it progresses through the lifecycle.

“We are delighted that our team of wireless networking researchers has been selected to take the lead of the PAWR Project Office in partnership with US Ignite, Inc.,” said Dr. Nadine Aubry, dean of the college of engineering and university distinguished professor at Northeastern University. “I believe that PAWR, by bringing together academia, industry, government and communities, has the potential to make a transformative impact through advances spanning fundamental research and field platforms in actual cities.”

The PPO will work closely with NSF, industry partners and the wireless research community in all aspects of PAWR planning, implementation and management. Over the next seven years, NSF anticipates investing $50 million in PAWR, combined with approximately $50 million in cash and in-kind contributions from over 25 companies and industry associations. The PPO will disperse these investments to support the selected platforms.

Additional information can be found on the PPO webpage.

This announcement will also be highlighted this week during the panel discussion, “Wireless Network Innovation: Smart City Foundation,” at the South by Southwest conference in Austin, Texas.

Sheikh Mohammed bin Rashid Al Maktoum at the competition launch. Image: uae4goodawards/instagram

The first UAE Artificial Intelligence and Robotic Awards for Good aim to encourage research and development to meet challenges in the health, education and social services sectors. But less than two weeks remain to enter the contest, where individuals, teams, universities and companies from around the world can all compete for £1m in prize money.

The Robotics for Good Awards follow the UAE’s successful 2014 Drones for Good competition and were launched earlier this year by the Crown Prince of Dubai, Sheikh Hamdan bin Mohammed bin Rashid Al Maktoum, who is also chairman of the Dubai Executive Council.

“The UAE’s journey in innovation is gaining a national momentum every day,” he said. “We are confident of our abilities and the vision of our leaders to achieving a leading position in the world in the field of innovation. Our goal is to harness science and technology to promote a better life for the people and enhance happiness in the communities.”

Mohammed Abdullah Al Gergawi, Minister of Cabinet Affairs, and chairperson of the Organising Committee, added: “The award aims to honour the best application of robotics and artificial intelligence in the service of humanity with a focus on three key areas: Education, Health and Social Services.”

Al Gergawi said the competition will be managed by a committee comprising specialists in robotics and artificial intelligence technology to assess the ideas and projects.

“The competing robots must be compliant with safety standards, incorporate latest technologies, and characterized by high reliability while assuring value-added services.

“The participants will propose the type of services that these technologies will provide, for instance in helping people with disabilities, treatment of patients, encouraging children in education, as well as complex tasks such as fire-fighting, construction work and social care.”
The competition forms part of the UAE’s plans to make 2015 the Year of Innovation. The winners will be announced at a ceremony in February 2016, ahead of the fourth Government Summit in Dubai.

More information can be found at www.roboticsforgood.ae
The deadline for entry is 31 October 2015

We’re excited to announce that OSRF and BIT Systems are seeking innovative and revolutionary robotics projects for the Robotics Fast Track (RFT) effort, sponsored by the Defense Advanced Research Projects Agency (DARPA).

The goals of Robotics Fast Track are to:

1. Enable rapid, cost-effective development of new robotics capabilities for space, sea, land, and air applications. RFT will focus on the development of groundbreaking robotic hardware and software by funding novel approaches as well as creative adaptations of existing technologies.
2. Achieve breakthrough capabilities in less time and at a fraction of the cost typical of government-supported robotic development processes by engaging highly agile organizations and individuals who traditionally have not worked with the U.S. government.

Anyone can apply for Robotics Fast Track funding, both US and non-US organizations.  Learn more and apply at rft.osrfoundation.org!

Rich Walker, Managing Director, The Shadow Robot Company

The Shadow Robot Company has been perfecting its robot hands for almost two decades, but it took just a short demo by the world’s first robot chef last month to propel this small, London-based startup into the global limelight. Despite the chef’s obvious attractions, Robohub’s Adriana Hamacher wanted to delve deeper: to discover what future robot hands have in the manipulator market and why they could soon turn up in a strawberry patch.

With his waist-length dreadlocks and goatee, Rich Walker certainly stands out at the funding and robo-business events, where I’ve often bumped into him. His workshop is just down the road from my house, so when the robot chef was unveiled at Hannover Messe last month, cooking up a storm for the world’s media, it seemed like a good time to pay Rich a visit.

Despite its prowess at making crab bisque, it’s fair to say that the robot chef is defined by its highly sophisticated manipulators – the “Dexterous Hands” in which Shadow specialises.

But the project is actually a collaboration between Shadow and Moley Robotics, the company funding the venture. Last year, in order to fulfil his vision of creating a chef replicator, Moley’s Russian-born founder, scientist and engineer Mark Oleynik, went on the hunt for a company to build the hands for his robot kitchen. He found there was a fairly short list, and it really only came down to one company: Shadow.

“What we built was almost a classic piece of industrial automation,” says Rich, taking up the story. “It’s a couple of robot arms with tooling on the end to be able to interact with a set of well-defined, fixed objects and perform a complex procedure with them. It just happens they’re in a kitchen, the tooling is a pair of fully human-like robot hands and the procedure they’re performing is cooking a crab bisque – it takes 26 minutes. The things you start with are not nuts and bolts and metal flanges, they’re chopped garlic and chicken stock, and the end result is a bowl of soup, plated up exactly as a chef would do it.

“And it’s worth noting that every single person in this company now knows how to cook a crab bisque, because we’ve seen it done seven million times!”

Masterchef winner Tim Anderson, preparing crab bisque. Source: Moley Robotics

The now infamous crab bisque recipe was prepared copying the exact movements of 2011 BBC MasterChef winner Tim Anderson. The robot switches on a hob, scrapes butter into the pan and adds prepared and measured ingredients – from a specific place on the worktop. But, it doesn’t do the chopping… That, says Rich, is an AI problem.

For Rich, corner cutting or finding ways around the problem is second nature, as becomes increasingly obvious in our conversation. Not only is he able to solve problems, he’s also able to turn them to his advantage. Rich believes that supermarkets will want to supply ingredients for the robot kitchen – at a cost, of course – and it’s already becoming common to see chopped salad, vegetables and meat on a shop’s shelves.

Even without the chopping there’s still a lot to do, to get the chef ready by 2017 and by far the biggest challenge is that something like this has never been done before.

“Nobody has built a mass manufacturable humanoid hand,” says Rich. “We have to go from making a small number a year, for state-of-the-art research to something we could have a factory producing in large numbers. So that’s the longest arch of the project, the critical path.”

The robot chef in action. Source: Moley Robotics

The team is also looking at equipment options and trying to keep costs down. But there’s no denying that at around £10,000 ($14,000) – the robot chef will have a hefty price tag, although it’s effectively a complete kitchen, comprising an integrated oven, hob, dishwasher and sink. The market for consumer and office robots is predicted to  grow at a CAGR of 17% between 2014 and 2019, seven times faster than the market for manufacturing robots, so does Shadow’s boss think it’s an area ripe for disruption?

“It’s interesting that domestic robotics has been the thing that inspires people,” says Rich. “But there’s never been anything above the level of the vacuum cleaner. Part of the reason for this is that, when you talk about unstructured environments, homes are about as unstructured as you can imagine. They’re full of random things, things are never where anybody left them, there are small animals running around, there are children, there’s jam – all kinds of things that are really difficult for a robot to see, interact with and understand. And it’s very hard to paint a white line around it and say ‘nobody cross that white line while the robot’s running.’ A factory’s actually a really nice clean, safe, structured environment, when compared with a domestic one.

“Frankly, we’re still a long way from solving the really big problems there. The kitchen is interesting because, there, we’ve constrained it down and said: ‘we’re going to put this robot in the kitchen, above the kitchen, as part of the kitchen; it’s going to be part of the equipment, not wandering around the house. It doesn’t have to find things, it doesn’t have to avoid people, it’s just either the robot is running, in which case the kitchen is closed, or the kitchen is open and the robot is tucked away. So that’s a fantastic simplification, it kind of eliminates all the real challenges of robots in the home.”

“Nobody has built a mass manufacturable humanoid hand. We have to go from making a small number a year, for state-of-the-art research, to something we could have a factory producing in large numbers”

Rich Walker started off as a computer scientist and joined Shadow in 1989 to write software for robots, but he discovered the robots needed building first. He now leads the company, having taken over from founder and non-executive director Richard Greenhill. In the early days, in the mid-90’s, Shadow were primarily working on biped robots and soft pneumatic muscles, but it became apparent that things weren’t working out.

“Bipeds are, I hesitate to say, useless,” says Rich cautiously. “It’s very hard to see an application for a biped that’s commercially viable at any point in the next 10 years. Twenty years ago even more so, because you just need so much infrastructure and ecosystem and capability to make it worth having a hugely expensive biped robot that is risky and might fall over.”

So, they put their heads together and the concept of the human hand came up. That was nearly twenty years ago. So why has it taken them so long?

The Dexterous Hand. Source: The Shadow Robot Company

“We’ve been looking around at ways to get additional resources,” explains Rich. Shadow has become adroit at not only slotting its technology into the supply chain, but also fitting it into funding schemes in both the UK and the EU.

Some of the first applications for their hand included assistive technology. But, fifteen years ago, most of the other elements necessary – for the hand to be able to see, to navigate, to interact with objects and to communicate – were simply not there, which was a big problem.

Recently, Shadow has revisited this space; it’s involved in a European project, RAMCIP, building an assistive robot for people with mild cognitive impairment. With advanced infrastructure, it’s now possible to enable a mobile robot, with a hand, to navigate via 3D mapping, to sense people’s emotions and handle objects. No one calls them crazy anymore.

Applications in manufacturing are looking equally attractive, with the possibility of integrating the Dexterous Hand in a new generation of lightweight, relatively mobile, flexible and safe factory robots. The price point works too, as it’s comparable to the two-year fully loaded labour cost of an employee on a factory line.

“There’s a lot of people with automation type problems who are solving them by having humans do the work,” says Rich, “because you can’t get a traditional robot to do them. But this next generation, of flexible, dexterous, manipulation capable robots, should be able to make an impact on that.”

With both the domestic and industrial markets to consider, you’d think Shadow would have its hands full (pardon the pun), but there’s another sector beckoning too.

“If you can pick the fruit then all the other things can be improved and adapted, but today, there are no machines that you can use in the UK to pick fruit.”

Shadow’s business model is opportunistic in that the company looks for strong partners who have problems and European or UK funding calls to provide the finance to solve those issues. The big challenges are addressed, largely, with EU funding. For shorter term, more commercially focussed or more manageable problem areas, they target government agencies such as Innovate UK, assuming the partner organisation is UK-based.

A recent example is a joint Innovate UK and Biotechnology and Biological Sciences Research Council-funded agri-tech project the company is involved in, AUTOPIC. Led by the UK’s Harper Adams University, the project consortium includes BerryWorld, which  is the leading supplier of berries to UK supermarkets.

Modern strawberry trestles. Source: AUTOPIC Consortium

As might be expected, BerryWorld suffers from seasonal labour issues. The company is also very open to new technology. It’s already using innovative techniques that involve raising the growing area so that the strawberries are now waist height and rest on substrates instead of soil. Rich believes that this is a game changer; it’s opened the door to automatic harvesting.

“We actually focused on the commercial step changes,”he says. “If you can pick the fruit then all the other things can be improved and adapted, but today, there are no machines that you can use in the UK to pick fruit.”

He believes that previous solutions have over complicated the process. “They’ve been very interested in problems like: ‘how do you see the berry in a complex space?’ The whole research challenge.”

But modern day farming means that strawberry trestles are now managed in such a way that it should be – not easy – but more possible for a robot hand to access the fruit:

“The leaves are raised up so they’re out of the way and the berries hang down so they’re very, very visible. The challenges are getting to the less accessible fruit at the back, not damaging the plant and not colliding with things, while doing it all at speed – picking a strawberry every four or five seconds – to have a chance of being commercially viable.”

The system must also only pick grade one fruit, because, unlike apples, for instance, strawberries won’t ripen after they’re picked.

There’s an impressive amount of technology involved in Shadow’s hand: 20 motors, 26 micro-controllers, 24 movements and 129 sensors. So, just how close is it to a real human one?

“We’ve managed to capture almost all of the interesting capabilities,” says Rich.  “Human joints have a property of dislocating and relocating and we don’t do that. The human hand, because of the way the bones run through the palm, can do this kind of wrapping and curling activity. What we do on our robot hand is just a finger bend that comes up to oppose the thumb, rather than a natural wrapping and curling. But, other than that, we think we’ve pretty much captured all of the detail of the way the human hand works. We haven’t yet got anything like the sensitivity of human skin and finger tip sensing. I think it’s going to be another decade before you have all-over high resolution sensing. But, in terms of the mechanical movement and operations, we seem to have about the same sensitivity, the same precision and better repeatability, because it’s a robot. We haven’t found any manipulation task that, if we could program it, we couldn’t use it so for.”

What stands out from talking to Rich is just how multidisciplinary the work Shadow does is; it’s not just about the hands, the software, the hardware, 3D navigation and AI, it’s about supply chains, dealing with chefs, users and funding bodies. How would Rich advise a young start-up to approach all the work that needs to be done to get something like this off the ground?

The Dexterous Hand. Source: The Shadow Robot Company

“We’ve already done robot kitchens so find a different problem,” he quips. “There is a lovely concept that you get taught in business school: it’s the cycle of resources and the cycle of constraints. You say: ‘I want to do something, what have I got to make available to me? How well do I understand the problem I’m trying to solve?’ If you don’t have enough resources, there are two things you can do. You can either go out and raise money, bringing partners in, developing technologies… or you can iterate on a loop of understanding the constraints and refining them around the problem. That means saying things like: ‘suppose the ingredients are supplied in package form, so that we don’t have to chop them. Is that feasible? Yeah, great. So, we’ll do that.’

“So you simultaneously increase the amount of capability that you have and decrease the problem, until you hit the sweet spot, where you say: ‘I have enough resources and the problem is well enough constrained.’ It’s iterating on those two loops that gets you from: ‘I have an idea and I’m going to need £100 million to do it and I don’t know who the customer is,’ to: ‘I can see all the customers, I’ve actually met most of them, the problem is well constrained, I only need two external partners, I know who they are and I’ve got some funding to execute the project.’ It’s all achievable and everyone we need is in the room.”

He makes it sound so easy. But anyone who’s attempted to build a robot of any complexity will know that it’s not. However, it is possible, and the robot chef, with his hands that were nearly twenty years in the making, is testament to that.

If you liked this article, you may also be interested in:

• 2015 sees mobile manipulators coming to market
• Governmental funding of strategic robotic projects
• OpenBionics prosthetic hands: Open source, affordable, lightweight, anthropomorphic
• DARPA’s HAPTIX project hopes to provide prosthetic hands with sense of touch
• Grasping objects in a way that is suitable for manipulation

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

From the 2014 archives of The Robot Report: 30 fundings, acquisitions, IPOs and failures with some staggering figures. UPDATED Jan 20, 2015 to include additions from Travis Deyle’s Hizook blog, and on January 7 to include Rethink Robotics equity funding and the acquisition of RobotWorx. 

[All citations below can be found in the 2014 archives of The Robot Report or by searching in the red search box on the menu bar above.]

$1.08+ billion in Acquisitions:

• Deepmind was acquired by Google for $643 million;
• Swisslog was acquired by Kuka for $357 million;
• Titan Aerospace got $60 million;
• Infotron got $10 million;
• RobotWorx got $7.7 from NZ Scott Technology;
• and Reis Robotics, Airbotix, Novauris, Softeo and EMU all got acquired for unknown amounts.

$101.1+ million in IPOs:

• ReWalk got $36 for their IPO;
• Ekso $30.3;
• Titan Medical $34.8
• and Cyberdyne got an unknown amount.

$424.2 million in equity fundings (seed, crowd, series A,B,C,D, VC, etc.):

Large and small — but steadily throughout the year, all types of funding for robotic startups and spin-offs occurred during 2014.

Many got large fundings:

• Anki got $55 million in Series C funding*;
• Restoration Robotics got $45 million*;
• Airware got $25 million;
• Vicarious got $12 million;
• Rethink Robotics got $26.6;
• Medrobotics got $46 (in two separate fundings);
• Arago got $55;
• Corindus $26;
• Skycatch $16.4*;
• Persimmon Technologies $15.2*;
• Qbotix $12*;
• Kespry $10*;
• Mujin $6*;
• Remotive $5*;
• Knightscope $6.7;
• PrecisionHawk $10;
• Orbotix got $21.1; and
• Play-i got $8.

Smaller fundings included:

• JIBO at $2.2 million (IndieGoGo);
• Monsieur $2;
• Railpod $2.5*;
• Zano $3.5 (Kickstarter UK)
• Virtual Incision $4*;
• Modular Robotics $3.1*;
• Riverfield $2*;
• Cyberhawk Innovations $1.9*;
• Savioke $2*;
• EMU $1.5 but was later acquired by Google;
• Hibot $3.1; and
• Ozobot $2.

Failures:

• Seegrid filed for bankruptcy to reorganize if at all possible
• Unbounded Robotics closed up shop for lack of funding

Microsoft has been investing in Swiss research for years, and now the US technology company is renewing its longstanding collaboration with EPFL and ETH Zurich. Microsoft will provide one million Swiss francs per year in funding for IT-related research projects at the two universities over a period of five years. The collaboration is a continuation of a project launched in 2008 that focused on embedded technology software solutions and prototypes. The new collaboration will now broaden the areas of computer science and deepen the collaboration between the three partners.

Scientists in Lausanne and Zurich submitted 27 proposals, seven of which were selected by the steering committee. Among the successful projects:

Interacting with flying robots

Otmar Hilliges, a 34-year-old assistant professor, is one of the successful project applicants. The young computer scientist from ETH Zurich studies the interaction between people and computers. For his project, he and Dr. Shahram Izadi from Microsoft Research are investigating how flying robots can work and interact with people in active scenarios. Specifically, they want to develop a platform that enables flying robots to do more than just recognise people and navigate their way around them. Thanks to their algorithms, the robots should be able to react to gestures and touch as well.

Energy-efficient memory systems

At the EcoCloud center at EPFL, Dr. Edouard Bugnion and Professor Babak Falsafi are carrying out research into energy-efficient memory architectures for data centres that can handle huge amounts of data. To do this, they are combining thousands of energy-efficient micro-servers in a way that enables them to access the memories of the other servers with a minimal time delay. The two computer scientists are working with Dr. Dushyanth Narayanan and other scientists from Microsoft Research in Cambridge to develop new applications for this system, known as Scale-out NUMA.

Link to audio file (25:51)

In today’s episode Per Sjöborg speaks with Jan Westerhues, Investment Partner with Robert Bosch Venture Capital, about how they fund robotics companies. As a stepping stone towards their long-term goal of building autonomous cars, they are currently investing in a wide range of robotics technologies with real world applications. Westerhues talks about when in a project’s life they can help, and what to expect throughout their involvement. He also promises exciting news in the coming months, so stay tuned.

Jan Westerhues
Jan Westerhues is Investment Partner with Robert Bosch Venture Capital in Frankfurt, Germany, where he is responsible for robotic investments. He is also a board member/observer at Aethon (USA), as well as at a soon-to-be-disclosed low cost autonomous navigation company in the EU. RBVC is the corporate venture arm of Robert Bosch GmbH, one of the largest private conglomerates with over 50 billion Euros sales. The VC fund invests in start-up companies  worldwide either directly or via Venture Capital Funds. Investment focus is technology companies that fit Bosch’s current and future business. RBVC provides capital for minority stakes in start-ups from early to expansion stage. Prior to this position, Jan was responsible for Bosch Corporate Strategy in the Asia Pacific region, based in Shanghai, China. He gathered extensive experience in strategy consulting before joining the Bosch Group. Jan holds a degree in engineering and business administration (Dipl.-Wirtsch.-Ing.) from the Technical University of Darmstadt, Germany and is a CFA charter holder. He speaks German, English, and Spanish fluently and has a basic knowledge of Mandarin.

Links:

• Download mp3 (15.3MB)
• Subscribe to Robots using iTunes
• Subscribe to Robots using RSS
• Robert Bosch Venture Capital

Link to audio file (31:13)

Diana Saraceni is a Venture Capitalist at 360 Capital Partners. In this interview, she tells us about her first investment in robotics 3 years ago with Invendo Medical, and her views on how the market has changed since then. Hardware is now perceived as less risky, even though it is more challenging to scale than software. Recent success stories have further helped promote VC funding in robotics.

Saraceni discusses the importance of the founding team, as well as their advisors, for the success of a company. Finally, she shares her view on open source vs. proprietary technology from a venture capitalist’s perspective.

Diana Saraceni
Diana Saraceni is a partner at 360 Capital Partners, a Pan-European Venture Capital firm. Before becoming a Venture Capitalist in 2001, she was Senior Advisor at Lazard Investment Banking. At Lazard she was part of the Technology Team and primarily worked on M&A transactions and IPOs. Prior to Lazard, Saraceni spent several years as strategic consultant with A.T.Kearney in Milan and London. She was/is part of several national and international start-up selection committees and holds a degree in Engineering from the University of Rome and an MBA from LUISS.

Links:

• Download mp3 (19.5MB)
• Subscribe to Robots using iTunes
• Subscribe to Robots using RSS
• Diana Saraceni
• 360 Capital Partners
• Invendo Medical

… Neato Robotics – the NJ-based competitor with iRobot’s Roomba vacuum cleaner – raised $14 million in new funding from two VC firms. In 2012, Neato raised $12.2 from two different VC companies.
… PrecisionHawk closed an undisclosed-amount of A-round equity funding led by Bob Young (co-founder of Red Hat) and Innovate Indiana, the VC fund of Indiana University. This comes on the heels of May’s rebranding from Winehawk Labs to Precision Hawk and their focus on the collecting, interpreting and handling of the data, not the platform.

With the rapid economic development of the last twenty years resulting in the accumulation of great wealth, China urgently feels the need to move from a manufacturing-driven economy to an innovation-driven one. As a result, China is supporting many bold research initiatives in an effort to develop and attract the highly skilled individuals who will be needed to lead this transition. Thanks to recent dramatic developments in hardware and software, economists anticipate that the Chinese robotics industry will meet its spring season this year.

Every five years, the central government of China releases a new Five Year Plan, which establishes the core concept of development in all areas of Chinese society. In 2011, China started its 12^th Five Year Plan, and for the first time ever, the service robot was ambitiously identified as an important area for development. As such, it is anticipated that many new Chinese robotics companies will emerge in the near future to meet the growth targets set out in the plan.

However, due to the economic crisis, the situation is changing subtly. I traveled around several main cities in China in early 2013 to learn from experts in the current automation industry, and it was apparent that because the new generation of Chinese workers asks for higher pay and lower workloads, it is very difficult for China’s massive manufacturing industry to recruit new workers. Not surprisingly, leading foreign industrial robot companies, such as Kuka, ABB, and Fanuc are taking advantage of this problem to actively market their robots to the manufacturing sector.

Local companies are likewise developing Chinese industrial robots that may have relatively low performance, but which are nonetheless able to meet industrial requirements. One such example is the Million Robots Project from the Chinese electronics manufacturing giant Foxconn. Yet, while the industrial robot market is growing, service robots still remain the province university labs and research institutes.

Funding high risk research in China
In China, almost all high-risk, high-reward research is conducted by central government agencies: the National Natural Science Foundation of China (NSFC), the Ministry of Education (ME), the Ministry of Science and Technology (MST), and the Organization Department of CPC Central Committee (ODCCC).

NSFC aims to support outstanding young researchers through the awarding of modest grants from the Young Scientists Fund. This is the most popular funding mechanism for young researchers when they first begin conducting independent research as it is relatively easy to apply for and receive. The Ministry of Education manages several projects, such as the Research Fund for the Doctoral Program of Higher Education of China (for new teachers), and the Chang Jiang Scholars Program (CJSP), which is supported by the Program for New Century Excellent Talents in University (NCET). For example, the CJSP tends to recruit top young and mid-career researchers both in and out of China to work as academic leaders, and awards sizeable grants to them.

The Ministry of Science and Technology manages several projects that are significant to researchers engaged in high risk, high reward research, including the National Basic Research Program of China (973) and the National High Technology Research and Development Program of China (863). The influence of 973 and 863 on Chinese scientific research is far-reaching, and only top-tier professors with excellent teams are considered for funding by this elite program. Because research funded by these projects is carried out by large groups of people, 973 and 863 usually give out significant funds, in the order of millions of dollars depends on the scale of the project.

The ODCCC funds high-risk research initiatives through the Thousand Talent Project (TTP), a three-year term project with possible extension. The goal of the TTP is to recruit thousand of foreigner researchers with strong expertise in hardware and software to help develop innovation in China. There are already more than 100 foreigner researchers working in China since 2008, the year TTP started, including Prof. Toshio Fukuda, a former IEEE RAS president, director of the IEEE Division X, who was invited to Beijing Institute of Technology (BIT) to work on Micro-nano research.

Where the money goes
It can be difficult for people outside of China’s borders to learn about the projects these granting programs support because, due in part to language barriers and visa restrictions, Chinese researchers tend to participate in domestic conferences rather than international ones.

Yet while robotics researchers from around the world keenly watch videos of Boston Dynamic’s Bigdog walking freely on uneven and slippery mountain roads, or Honda’s Asimo dancing and hopping on one foot, the Chinese government is also busy establishing similar projects in a more low key fashion (see this PlasticPals YouTube playlist for a fair sample of what the whole must be).

Having visited Chinese laboratories and spoken face-to-face with researchers, I have witnessed several bold Chinese robotics initiatives that are currently underway. One particularly challenging area of development is the humanoid robot, and two of the best robotics laboratories for this in China are at the Beijing Institute of Technology (BIT) and Zhejiang University (ZHU), both of which have succeeded in producing the first humanoid robots that can perform Tai Chi and play Ping-Pong (see here and here). These robots were not specifically designed for game play – they were in fact developed as part of China’s domestic service robots initiative – but Tai Chi and Ping-Pong have helped researchers to test their robots’ image processing and dexterity.

I visited BIT’s robotics lab this past April, and saw their BHR-4 and BHR-5 humanoids in action. Using cameras couple with high-speed image trajectory processing software, a pair of BIT’s BHR-5 Humanoid can rally at Ping-Pong up to 200 times without error. The BHR-5s stand 162 cm (5’4″) tall, weigh 63 kg (139 lbs), and have 32 degrees of freedom. With its realistic animatronic face, BIT’s BHR-4 Humanoid, on the other hand, is more focused on conveying a variety of emotions that on speed and gross-motor dexterity. It reminds me of Prof. Ishiguro from Osaka University, Japan, who is the world leading robotics researcher in building humanoid robots with lifelike appearance and visible behaviour. The BHR-4 stands 170 cm (5’7″) tall, weighs 65 kg (143 lbs), and thanks to all the moving parts in its face, has an incredible 43 degrees of freedom.

China is also pursing its own version of BigDog. In 2011, the 863 program established another 3-year project with funding up to $700US million that aims to build a Biomimetic Quadruped Robot like Boston Dynamic’s BigDog. Almost all the important robotics labs in Chinese universities are competing for this funding. The Harbin Institute of Technology (HIT), Shanghai Jiao Tong University (SJTU), Sheenyang Institute of Automation Chinese Academy of Science (SIA-CAS), Shan Dong University (SDU), and other universities and institutes each released their version of BigDog one after another.

These homegrown initiatives may not yet have the performance capabilities of their better-known counterparts, but the Chinese are well on their way to catching up to the world leaders in robotics research.

With contributions by Hallie Siegel.

If you liked this article, you may also be interested in:

• Swiss to invest almost CHF30 million in digital fabrication research over next 4 years
• Robot tourism coming soon to Korea: Masan Robot Land project finally breaks ground
• Russia looks inward and outward at Moscow’s 2013 Open Innovations Forum
• Long view required to keep economic policy in step with developments in robotics

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

Often funding sources – the groups taking the risk – are not the beneficiaries of the rewards of the venture. Intuitive Surgical is an example.

NSF, DARPA and NASA funded a project to solve a very real problem: providing medical attention to Americans in remote places such as space, war or scientific expeditions. The initial concept was to be a telepresence project but with no known solution. That was the high-risk research project funded by the three agencies.

During the development phase, two enterprising team members, Frederic Moll and Robert Younge, concluded that true remote-presence surgery couldn’t be achieved with then-current technology but could be achieved within a controlled network,and by so doing there would be many benefits to the surgeons and patients involved. The two wrote a business plan, got venture money and proceeded to develop the system now known as the da Vinci Surgical System within a company subsequently named www.

Shortly before going public, and before getting FDA approval, Intuitive Surgical was sued for patent infringement by Computer Motion, Inc., which had its own system, the ZEUS Robotic Surgical System – a system which was already approved for use in Europe.

The litigation was resolved in 2003 when the two companies agreed to merge, thus ending the litigation. The ZEUS system was ultimately phased out in favor of the da Vinci system. The litigation created an active depository of intellectual properties – hundreds of patents and trade marks – that Intuitive Surgical has vigorously defended in a way that has created a competitive void in the commercialization of similar devices and systems.

Consequently Intuitive Surgical has grown to be a growth company with large profits and is listed on the NASDAQ stock exchange (NASDAQ:ISRG). But it didn’t exactly happen with the high-risk / high-reward formula. Intuitive Surgical and it’s VC backers got the reward and NSF, DARPA and NASA are still searching for their solution.

SRI and Stanford University did get money for licenses to use the technologies they developed, but not the huge rewards stemming from the successes of Intuitive Surgical.

As is often the case in startups, the solutions and products that finally emerge in the marketplace are ones that are different from those that initiated the startup. Sometimes this involves changes in funders, partners and ownership and those that reap the final rewards are often removed from the originating project.

High risk takers are most often governmental agencies with a strategic social/political issue to resolve. Corporate R&D departments also invest in future scenarios but to a lesser extent – they most often pragmatically acquire the technology they need and rework it to fit their specific requirements.

Hence the dilemma: does the initial risk taker expect to get the double reward of (1) product solution and (2) profits from their sale, or just the altruistic reward of seeing that their initial problem, for which they are risking their money, is being addressed in the broader marketplace solving the original problem, reward or not?

Over the last 20 years or so, a sense that science has become conservative or incrementalist has developed, and calls for change in the approaches to public funding of research have been heard from various quarters. Several notions have been suggested of what should be supported instead of “normal science” or “incremental innovation.” Among them we have heard calls for more “high risk-high reward” research, or for more “highly creative” science, or for more “cutting edge” or “frontier” research and, more recently in language adopted by funding agencies, that more “transformational research” is needed.

The main idea is that there isn’t enough risk taking, and little scientific or technological creativity is reflected in proposals that might “revolutionize” our understanding of the nature or society. “Business as usual” in the support of science and technology seems not to be satisfactory for producing the sort of radical change and rapid advance in science needed to solve important problems we face in economic development, health care and general social wellbeing.

This discussion does not fully address the situation in the private sector. However, the fate of many top-performing R&D centers in companies such as IBM, Texas Instruments, AT&T, among others, over the same period indicates that corporate willingness to take risks in research is not precisely at its most adventurous. Having said that, our focus here is on public funding since the sense of risk and reward of innovation by private industry in the market does not have the severe principal-agent problem faced by public funding. Companies invest their own money and either lose it or make a profit for themselves. Researchers funded by government do not lose their own money in the risk taking. The government takes virtually all the risk, at least in the financial sense.

When it comes to radical innovation in robotics, this distinction about risk taking must be kept in mind. In any case, the participation of the public sector in the development of robotics technology has the purpose of reducing the risk for private companies that, without at least partial subsidies from government, would not have a safe enough business case to get involved. This is the well-known market failure justification for public support of R&D.

In the context of public funding, the capacity of the government to take on R&D risk is not infinite. And moving from the intuition on the desirability of more scientific and technological breakthroughs to a clear understanding of how it would be recognized, what exactly is the difference between incremental research and proposals for future scientific revolutions, and what the proper incentive and support mechanisms are for it has proven difficult. It is not clear what in the research process has the attribute that is looked for. Is it the projects that are special? Are certain scientists capable in a different way? Is it the organization that can provide an unusual environment for research? Or is it groups of projects, that is, portfolios that must be assessed for their combined effects? So far, none of these questions has a clear answer.

Models, Metaphors, Analogies to Produce Meaning
One way to begin to clarify the problem is to take the models that are being used either implicitly or explicitly to suggest courses of action. We have identified at least four that have appeared repeatedly in documents and speeches about the “special” research that might have higher impact. They work as analogies for highlighting one or more important attributes or their consequences. These are the models of stock investment portfolios; biological evolution; “hot” trends; and exploration of the wild.

Stock Investment Portfolios
Many calls to support more “high risk” research that has the potential to offer “high reward” appeal to the intuition of investment risk. In this analogy, each project that is up for support is similar to a stock considered for inclusion in an investment portfolio. As in stock portfolios, a balance of risk is sought across the portfolio so that a number of safer bets compensate for riskier ones that might payoff disproportionately.

The important implication of this perspective on research support is that the unit is the project and that each one is assessed in comparison with the others in the portfolio. The overall balance of risk of a good portfolio means that projects are not selected on the same criteria. Some will be “good” low risk projects to compensate for potential losses of the high risk ones. This is clearly not current practice in public funding of research since all projects are assessed on the same criteria and only the best are funded. All projects have approximately equal risk.

There are a few consequences that must be given further thought. First, what attribute of projects must be risk assessed on? Are risks across disciplines considered, for example? Or are risks across organizations or types of projects? No clear answer to this question has been offered. Second, how much failure will be tolerated? If risk is real, then high risk means high probability of failure and a high failure rate should be observed. Otherwise, the risk is not as high as it was assumed. No clear answer for this question is available either. Much talk about “high risk-high reward” is superficial and really suggests that most high reward projects could be identified with some special assessment mechanism without a high risk of failure. Actual failure would probably be pinned on the proposal assessment mechanism rather than the risky nature of the projects.

Evolution in Science
This analogy implies that new ideas in science appear much like genetic mutations do in living organisms. If our selection mechanism allows for the more radical mutations to survive, more radical change in science would probably follow. Most attention has been drawn to the selection mechanisms, assuming implicitly that the size of the pool of variation for the chance of selecting viable large jumps is sufficiently large.

The consequences of this line of thinking are also intriguing. First, the necessity of a random generation of variation in scientific ideas is not a familiar one. The image of a rational scientific method has a strong cultural effect of keeping random idea generation hidden from view, if not largely muted. In other words, attention would have to be put on the environment that allows for a large pool of very diverse scientific ideas to emerge continuously in order to have large jumps that might be selected. Secondly, a large measure of randomness in the consideration of scientific ideas would have to be acceptable to the establishment. Otherwise, just as the reduction in biological diversity is a serious problem for environmental health, there will be very little to select from to have many “viable new scientific organisms.”

Hot Trends in Science
Science is not different from other cultural phenomena in that novel trends generate “icons” and “hits” that the community rallies around. As a matter of fact, many new ideas in science and technology are followed during the first period of their public diffusion to assess whether they are substantive or only a fad. It is often heard of researchers gaining prominence in their fields that they are new “stars” or that they are “hot.” These trends and their icons attract a following, and researchers that join the movement fashion their professional identity around the key features of the emerging field.

The main lesson to drive home from the analogy is that this cultural phenomenon is an integral part of science even if it is not formalized into the assessment of proposals and projects. Individual projects are not the main focus. The “movement” is the main concern. But, how does the perception of a hot trend and its icons affect the assessment of project proposals that promise to continue in its wake? How does the system deal with the possibility of a fad that wastes energy and resources on a trend that does not pan out? A rapid recognition mechanism to tease out indicators of faddish elements seems to be necessary to address this issue. But this would be a “conservative” reaction. Should the system be more liberal in embracing hot trends to avoid killing off potential revolutionary developments? This would be another type of risk that might have to be accepted. With its acceptance comes another departure from a common view of rational science that looks askance at enthusiasm and bandwagon effects as illegitimate passions. Maybe science should have a few “moments of madness”.

Exploration of the Wild (or the Endless Frontier)
The idea that science is a sort of exploratory venture into the unknown unexplored regions of nature is an old one. It was made into influential policy discourse by a prominent scientist in the aftermath of World War II: Vannevar Bush. It assumes that what we don’t know is contiguous with what we know, and we just have to “venture out” into this unexplored territory to get to know it. The only difference between conservative, incremental science and the highly creative or transformational research is that the exploratory journey should go deeper and farther into the unknown in one single expedition.

This image suggests that the main way to achieve sizable leaps to advance science is by organizing well-equipped and supported expeditions into unexplored territory. The skeptics in policy making recognize immediately that this analogy suggests that research always requires more funding: “If you give us more money, we can go deeper into the unknown.” This was already recognized as a subtext of the original idea of the “endless frontier.” Risk is downplayed in this analogy. Only underprepared expeditions are risky. There is always unknown territory to discover. The question is rarely raised that there may be little of value in vast regions of the unknown.

A Path Forward?

It seems that before we can define a path forward it is necessary to come to terms with the full consequences of what must be achieved. First, the simple formula of “high risk-high reward” hides the complexity of the goal. There are many interrelated issues that must be addressed simultaneously if this objective will be pursued with a committed effort. A simple set of criteria for evaluating proposals will not do the job. Second, a part of the public image of science as a highly rational activity is tied to the status quo of low risk incremental change in science. Higher risk and randomness that seem to be inherent in increasing the magnitude of change in science may open the enterprise to criticism and loss of legitimacy because of an appearance of irresponsible gambling with public resources. The idea is that the payoff of a few initiatives that succeed will compensate for many that fail. Is there any publicly supported system in today’s political environment that can operate legitimately under those conditions? Not likely.

The DARPA Robotics Challenge has an interesting approach to encourage the pursuit of “leaps forward” in the development of these technologies while reducing how much risk it takes on at any point in time. It does so with two crucial measures. First, it specifies a well defined target of technological capabilities. So, in terms of the metaphors we used, it is not looking at the entire evolutionary environment of technology or at the entire frontier of technology. It limits how much randomness must be accepted and how far into the unknown it may be necessary to travel before something of value is shown. Second, by making several teams compete in stages and granting a limited amount of funding to compete in progressively more difficult challenges, it reduces potential losses and requires the return of something of value before more risks are taken. At most, no team will advance to the next stage, so what has been granted will be lost, but it cuts its future losses as soon as nobody can show progress. However, the risk of pursuing those technological objectives rather than others has not been mitigated, and the stages might cut losses too early.

For this reason, in fields where objectives cannot be specified with such clarity, program design is more difficult. But the lesson remains. As the DARPA program shows, the flexibility may have to be transferred to the very support mechanisms themselves. Attempting to derive a fixed set of procedures and criteria to identify and support something that is highly variable, with an irreducible measure of randomness, culturally unstable and insatiably adventurous may be the wrong path to go down. The criteria and support mechanisms may have to become “experimental” themselves. The future development of scientific and technological research may be pressing for some institutional change.

National Science Foundation (NSF) efforts to develop a mechanism to fund research proposals that had a high risk of failure, but which also had the potential for high return, began in 1980. In that year a task force was created by the NSF Advisory Council to look at the issue of “highly creative or innovative” proposals for which there was “a high risk of failure.”

The task force’s report identified two significant hurdles the NSF needed to overcome to support high risk/high return proposals: 1) the conservatism of the peer review process, and 2) the reluctance of NSF program officers to fund research with a high potential for failure in an environment in which proposals with a high probability of success were not being funded because of limited budgets. The task force suggested a variety of ways to encourage NSF support of these risky proposals, most of which depended upon giving the program officer encouragement to use his or her discretion to identify and fund such proposals. None of the recommendations of the task force were immediately adopted by NSF, although some of the mechanisms suggested appear in modified form later.

The first NSF mechanism for supporting high risk proposals was developed in the recently created Engineering Directorate in the mid-1980s. Engineering took the initiative because of the leadership of Assistant Director Nam Suh, who felt that a small number of failed grants were a necessary and unavoidable by-product of efforts to fund innovative research. The Directorate was also responding to recommendations by the National Academy of Engineering for NSF support of high-risk/high- return research. Engineering established a pilot project called Expedited Awards for Novel Research (EANR), encouraging program officers to fund innovative proposals without the benefit of peer review.

The successes of EANR funded proposals persuaded NSF Director Erich Bloch to establish the Small Grants for Exploratory Research (SGER) mechanism for the entire NSF in August 1989. Restricted to no more than 5% of any program’s budget, SGER awards, like EANR awards, bypassed the external peer review process. There were a number of objectives for SGER awards, but one was to induce researchers to “propose high-risk work to NSF.”

In 2004, the National Science Board established a Task Group on High-Risk Research to reexamine the issue. Its work, and that of an NSF staff task force on the topic, led to the replacement of the SGER award mechanism by a number of other mechanisms in 2009. The most important of these for high-risk research was the Early-concept Grant for Exploratory Research (EAGER). An EAGER award will provide up to $300,000 for up to two years of “high-risk, high-payoff” research. Like its predecessors, EAGER awards do not require external review.

References
National Science Foundation Advisory Council, “Report of Task Group 10: Funding of Innovative High Risk Proposals,” November 6, 1980
“NSF Starts Program to Encourage Creative Engineering Research,” NSF PR85-74, December 12, 1985
Erich Bloch, “Small Grants for Exploratory Research (SGER),” Staff Memorandum O/D 89-11, August 14, 1989
Dian O. Belanger, Enabling American Innovation: Engineering and the National Science Foundation, 1998, p. 246.
National Science Board, “Enhancing Support of Transformative Research at the National Science Foundation,” May 7, 2007
National Science Foundation, “Proposal Award Policies and Procedures Guide, Part I: Grant Proposal Guide,” October 2012

The first pass seems to indicate that Boston is actually living up to the hype this year as it tops the list in number of deals and amount of funding and brings home the three largest deals.  Silicon Valley trounced the rest of the country on last year’s list with a similar performance to Boston’s this year.

Stay tuned for more analysis of the list once there is time for collective knowledge of the internet to complete the missing deals.

Public Expectations
Here’s a simple experiment. Ask a non-roboticist to give you an example of a robot — the first that comes into their mind. The odds are that it will be a robot from a Science Fiction movie: perhaps Terminator, R2-D2 or C-3PO or Data from Star Trek. Then ask them to name a real-world robot. Unlike your first question, which they will have answered quickly, this one generally needs a little longer. You might get an answer like “the robot in the advert that spray-paints cars” or, if you’re lucky, they might know someone with a robot vacuum cleaner. So, although most people have a general idea that there are robots in factories, or helping soldiers to defuse bombs, the robots that they are most familiar with – the ones they can name and describe – are fictional.

None of this is surprising. The modern idea of a robot was, after all, conceived in Science Fiction. Czech playwright K. Capek first used the word Robot to describe a humanoid automaton in his play Rossum’s Universal Robots (RUR) and Isaac Asimov was the first to coin the word Robotics, in his famous short stories of the 1940s. The idea of a robot as an artificial mechanical person has become a ubiquitous fictional trope, and robots have, for half a century, been firmly rooted in our cultural landscape. We even talk about people acting robotically and, curiously, we don’t mean like servants, we mean in a fashion that mimics the archetypal robot: stiff jointed and emotionally expressionless.

Furthermore, people like robots, as anyone who has had the pleasure of giving public talks will know. People like robots because robots are, to paraphrase W. Grey Walter, An Imitation of Life. Which probably accounts for the observation that we are all, it seems, both fascinated and disturbed by robots in equal measure. I have often been asked the question “how intelligent are intelligent robots?”, but there’s always an unspoken rider “… and should we be worried?”. Robot dystopias, from Terminator, to The Matrix or out-of-control AI like HAL in Kubrick’s 2001, make compelling entertainment but undoubtedly feed the dark side of our cultural love affair with robots.

It is not surprising then, that most people’s expectations about robots are wrong. Their beliefs about what real-world robots do now are hazy, and their expectations about what robots might be like in the near future often spectacularly over optimistic. Some think that real-world robots are just like movie robots. Others are disappointed and feel that robotics has failed to deliver the promises of the 1960s. This expectation gap — the gap between what people think robots are capable of and what they’re really capable of — is not one-dimensional and is, I argue, a problem for the robotics community. It is a problem that can manifest itself directly when, for instance, public attitudes towards robots are surveyed and the results used to inform policy [1]. It makes our work as roboticists harder, because many people think that the hard problems we are working on are already solved, and because it creates societal expectations of robotics that cannot be met. And it is a problem because it underpins the next expectation gap I will describe.

Press and Media Expectations
You are technically literate, an engineer or scientist perhaps with a particular interest in robotics, but you’ve been stranded on a desert island for the past 30 years. Rescued and returned to civilisation you are keen to find out how far robotics science and technology has advanced and, rejoicing in the marvellous inventions of the Internet and its search engines, you scour the science press for robot news. Scanning the headlines you are thrilled to discover that robots are alive, and sending messages from space; robots can think or are “capable of human reasoning or learning”; robots have feelings, relate to humans, or demonstrate love, even behave ethically. Truly robots have achieved their promised potential.

Then of course you start to dig deeper and read the science behind these stories. The truth dawns. Although the robotics you are reading about is significant work, done by very good people, the fact is — you begin to realise — that now, in 2013, robots cannot properly be said to think, feel, empathise, love or be moral agents; and certainly no robot is, in any meaningful sense, alive or sentient. Of course your disappointment is tempered by the discovery that astonishing strides have nevertheless been made.
So, robotics is subject to journalistic hype. In this respect robotics is not unique. Ben Goldacre has done much to expose bad science reporting, especially in medicine. But a robot is different to, say, a new strain of MRSA because — as I outlined above — most people think they know what a robot is. Goldacre has characterised bad science stories as falling into three categories: wacky stories, scare stories and breakthrough stories [2]. My observation is that robots in the press most often headline as either wacky or scary, even when the development is highly innovative.

I believe that robohype is a serious problem and an issue that the robotics community should worry about. The problem is this: most people who read the press reports are lay readers who — perfectly reasonably — will not read much beyond the headline; certainly few will look for the source research. So every time a piece of robohype appears (pretty much every day) the level of mass-delusion about what robots do increases a bit more, and the expectation gap ratchets a little wider. Remember that the expectation gap is already wide. We are at the same time fascinated and fearful of robots, and this fascination feeds the hype because we want (or dread) the robofiction to become true. Which is of course one of the reasons for the hype in the first place.

Who’s to blame for the robohype? Well, we roboticists must share the blame. When we describe our robots and what they do we use anthropocentric words, especially when trying to explain our work to people outside the robotics community. Within the robotics and AI community we all understand that when we talk about an intelligent robot, what we mean is a robot that behaves as if it were intelligent; ‘intelligent robot’ is just a convenient shorthand. So when we talk to journalists, we should not be too surprised when “this robot behaves, in some limited sense, as if it has feelings” gets reported as “this robot has feelings”. But science journalists must, I think, also do better than this.

Funder and Stakeholder Expectations
Many of us rely on research grants to fund our work and — whether we like it or not — we have to become expert in the discipline of grantology. We pore over the small print of funding calls and craft our proposals with infinite care in an effort to persuade reviewers (also skilled grantologists) to award the coveted ‘outstanding’ scores. We are competing for a share of a limited resource, and the most persuasive proposals — the most adventurous, which also promise the greatest impact while matching themes defined to be of national importance — tend to succeed. Of course all of this is more or less equally true whether you are bidding for a grant in history, microbiology or robotics. But the crisis of expectations makes robotics different.

There are, I think, three factors at work. The first is the societal and cultural context — the expectation gaps I have outlined above. The second is the arguably disgraceful lack of useful and widely accepted benchmarks in robotics, which means that it is perfectly possible to spend 3 years developing a new robot which is impossible to quantifiably demonstrate as superior to comparable robots, including those that already existed when that project started. And the third is the fact that policymakers, funders and stakeholders are themselves under pressure to deliver solutions to very serious societal or economic challenges and therefore perhaps too eager to buy into the promise of robotics. Whether naively or wittingly, we roboticists are I believe guilty of exploiting these three factors when we write our grant applications.

I believe we now find ourselves in an environment in which it is now almost de rigueur to over-promise when writing grant applications. Only the bravest proposal writer will be brutally honest about the extreme difficulty of making significant progress in, for instance, robot cognition and admit that even a successful project, which incrementally extends the state of the art, may have only modest impact. Of course I am not suggesting that all grants over promise and under deliver, but I contend that many do and – because of the factors I have set out – they are rarely called to account. Clearly the danger is that sooner or later funding bodies will react by closing down robotics research initiatives and we will enter a new cycle of AI Winter.

AI has experienced “several cycles of hype, followed by disappointment and criticism, followed by funding cuts, followed by renewed interest years or decades later” [3]. The most serious AI Winter in the UK was triggered by the Lighthill Report [4] which led to a more or less complete cancellation of AI research in 1974. Are we heading for a robotics winter? Perhaps not. One positive sign is the identification of Robotics and Autonomous Systems as one of eight technologies of strategic importance to the UK [5]. Another is the apparent health of robotics funding in the EU and, in particular, Horizon 2020. But a funding winter is only the most extreme consequence of the culture of over-promising I have outlined here.

Discussion
I want to conclude this talk with some thoughts on how we, as a community, should respond to the crisis of expectations. And respond we must. We have, I believe, an ethical duty to the society we serve, as well as to ourselves, to take steps to counter the expectation gaps that I have outlined. Those steps might include:

• At every opportunity, individually and collectively, we engage the public in honest explanation and open dialogue to raise awareness of the reality of robotics. We need to be truthful about the limitations of robots and robot intelligence, and measured with our predictions. We can show that real robots are both very different and much more surprising than their fictional counterparts;
• When we come across particularly egregious robot reporting in the press and media we make the effort to contact the reporting journalist, to explain simply and plainly the true significance of the work behind the story.
• Individually and collectively we endeavour to resist the pressure to over-promise in our bids and proposals, and when we review proposals or find ourselves advising on funding directions or priorities, we seek to influence towards a more measured and ultimately sustainable approach to the long term Robotics Project.

References
[1] Public Attitudes towards Robots. Special Eurobarometer 382, European Commission, 2012.

[2] Ben Goldacre. Don’t dumb me down. The Guardian, 8 September 2005.

[3] AI Winter. Wikipedia, accessed 14 March 2013.

Henrik Christensen on “What funding scheme is the most conducive to creating a robotics industry?”

The public should in most cases not subsidize companies. Tax payers should not be venture capitalists. The new wave of Lean Startup going around the world is a great model to ensure that …

Read more →

We hope you will join the discussion. Feel free to post your comment.

Credit: BARA, Statistics

The UK has world leading strengths in the underlying science and engineering contributing to these systems, and access to the markets that could exploit them.
All projects must be collaborative and led by a SME.  Projects will last up to 12 months and we expect total project sizes to be up to £133k although projects outside this range will be considered.

The Technology Strategy Board is an executive non-departmental public body (NDPB), established by the Government in 2007 and sponsored by the Department for Business, Innovation and Skills (BIS).

For more information about the project, please visit the TSB website.