Brain-computer interfacing (BCI) is a rapidly growing field that offers huge potential for many applications, such as medical grade BCIs to help people with sensory-motor disabilities. Currently, a number of researchers are developing more affordable BCI systems designed to address a wider range of neurotherapeutic applications.

Conor Russomanno is the founder and research developer of OpenBCI, a low-cost open-source hardware platform that records the brain’s electrical signals and uses devices and software languages to make the data easily accessible. Russomanno and co-founder Joel Murphy aim to accelerate the advancement of BCI through collaborative hardware and software development.

The OpenBCI project began earlier this year after raising over $200K through a Kickstarter campaign (more than doubling their initial goal). Even in the early stages, OpenBCI is already drawing a lot of attention and is having interesting repercussions in the BCI world.

“There’s a lot of really exciting stuff that’s going to happen in the near future and in the not so distant future, but I think the one thing that we’re hoping to achieve with open BCI is to really lower the barrier of entry both in terms of educational materials and also cost,” says Russomanno.

http://youtu.be/a55_EfFtysc

A number of consumer-grade EEG devices that have a relatively low channel capacity are available, but higher quality, medical and research grade EEG systems are much more expensive than a standard OpenBCI kit, which makes them less accessible. One of the advantages of Russomanno’s and Murphy’s development is that whereas previously, one medical grade system was used in a classroom or research laboratory, now, the same amount of money can be used to acquire  enough OpenBCI systems to provide every student with their own device.

“This is reflected in our consumer base. A huge proportion of our customers are students, graduate-level researchers and professors who want to use OpenBCI as a learning tool, explains Russomanno.

Another of OpenBCI’s exciting potentials is the fact that it is fully open source. Russomanno and Murphy are using a lot of their resources to create an infrastructure in which people are not just able to use the technology but can also share their experiences and connect with other people using the technology. This enables users to share tutorials, getting started guides and also their own individual projects. In this sense, the creators have not only provided a tool, they are also establishing a level of enthusiasm for an unprecedented unicentric development.

The fact that such enthusiasm is being drummed up in many sectors from academia to the business world, marks a big step for BCI. How far into the mainstream does OpenBCI have the potential to go?

“I think that to be realistic about the technology it’s important to realize that, especially in the commercial space, technology like this has a tendency to get mislabelled and misrepresented by media sources. When you see the catchphrase ‘mind controlled robot’ you think of someone sitting in a chair with electrodes plugged into their head having ultimate control over many, many dimensions of a robot’s functionality.” Says Russomanno.

In reality, however, in the current state, mind controlled robots, at least using OpenBCI, translates to looking at a flashing screen and having the frequency of the flashing induce a similar frequency in the brain, and then telling the robot to turn left.

“We’re are many steps away from wearing a device that knows what turning your car on, versus opening your door look like. So it’s important to be realistic about what the technology is capable of,” Russomanno explains.

Russomanno points out that for BCI to advance, it’s essential for people to work together. Although there is some competition within this space, he emphasizes the importance of cooperation. Progress from any one company is going to help the industry as a whole. People in tested in joining the OpenBCI community can buy the technology, make use of the many available resources and share their experiences and this will work toward pushing BCI forward into the future.

Image credit: 4bpblogspot.com

Link to audio file (23:28), or  listen on iTunes

In this interview, TechEmergence talks to Dr. Beata Jarosiewicz from Brown’s BrainGate project about the science of making sense of the brain’s inner electrical activity, and how the brain might be used to control a variety of devices if calibrated correctly. 

Researchers at BrainGate have given paralyzed patients the ability to move robotic arms and check emails with their thoughts alone – thanks to experimental neural implants in their motor cortex. Dr. Beata Jarosiewicz has been with BrainGate project for years, with a specific focus on interpreting neurological signals and turning them into actionable outputs.

The BrainGate Group is on the cutting edge of an emerging technology – brain-machine interfaces. Their advances have allowed individuals with extensive paralysis and locked-in syndrome to interact with the world around them by controlling a computer mouse with their mind. Moving a mouse is something that most of us take for granted, but an individual with locked-in syndrome, that is fully awake and conscious, has no other means of producing speech, move limbs, or make facial movements.

Through a device implanted in the skull, the BrainGate device interfaces with a computer, allowing the individual to interact with their environment. This technology is made possible in part by extensive mapping of the neural activity of the brain, but revolutionary hardware designed by engineers like Bacher have also been key.

Bacher began working on the BrainGate technology by conducting brain-machine interface research on non-human primates. Or, as Bacher describes it, “basically having monkeys playing video games with their brains.” This research helped Bacher and other researchers understand how the brain works and begin development of the assistive technologies. When the opportunity to join the BrainGate group presented itself, Bacher jumped at the chance.

Says Bacher, “Although I’m interested in the basic neuroscience and love the pure technology aspects of it, thinking about how this translates to improve the quality of life for people in the real world has always been the underlying motivation for me.”

Outside of his work on BrainGate, Bacher is passionate about connecting disabled individuals with assistive technologies. This passion led Bacher to found the Speak Your Mind Foundation, which creates, distributes, and supports assistive communication technologies for individuals who are unable to effectively communicate due to neurological injury and disease. Says Bacher, “there is still a huge gape between technology creators and healthcare providers.” Bacher hopes to help bridge this gap and bring these technologies to the healthcare market.

Bacher’s approach also takes worldwide emerging technology trends in hands-free computing, robotics, and other areas, and finds ways to translate them into helping disabled individuals. Using technologies developed for larger markets helps lower the costs in developing applications for assistive technologies.  While the technological solutions are currently tailored for specific individuals involved in clinical trials, the solutions developed for them have potential applications for larger groups.

Says Bacher, “if we develop a piece of technology for someone with a spinal cord injury who is moving their head to control a computer, there’s no reason that can’t help someone whose suffered a stroke.”

Human-computer interface technology is still largely limited to touch, keyboard, and mouse. The research conducted by Bacher and those like him has the potential to change this, and as these technologies progress, their potential applications widen.

Says Bacher, “clearly, a mouse and a keyboard, even today seems like an antiquated way to interact with technology. We’ve seen developments like touch-screen technology and voice-control come along way, but it’s still not mainstream. In order to really penetrate the commercial marketplace, there’s a high threshold for how well something has to work.”

While current research is focused on assistive technologies for disabled individuals, the possible applications don’t end there. Part of the reason for this is the “symbiotic” relationship developing between consumer and assistive technologies. Smart phones can provide the “brains” for assistive devices. Eye motion-capture technologies developed for paralyzed individuals open up new ways for the general public to interact with technology, and hands free technologies benefit individuals without the use of their arms. Bacher believes that technologies like Google Glass, Leap Motion, Kinect, and voice-control will continue to be refined, and eventually make the “leap” to widespread consumer acceptance.

It’s a process Bacher believes benefits everyone; with the potential to open up avenues of technological interaction considered the realm of science fiction only a decade ago.

When it comes to complex tasks like building a house, many people with different skills work together to accomplish a single, larger goal. Instead of trying to create a perfect robot capable of building a house solo, could scientists replicate how humans function and make a “swarm” of imperfect robots capable of working together to accomplish complex tasks? This is the question Dr. Jekan Thanga hopes to answer. Thanga is one of the leading researchers who are applying bio-inspired neuro-evolutionary methods to robotics, and heads up Arizona State University’s Space and Terrestrial Robotic Exploration Laboratory.

While the terms may seem like the stuff of science fiction, neuro-evolutionary methods actually take their inspiration from the world around us. Says Thanga, “neuro-evolutionary methods are inspired by the brain cells and nervous systems of multi-cellular organisms.” Neuro-evolutionary methods look at the “control systems” of living organisms and try to understand how they work. “We’re trying to understand the basics of how these individual cells work together as a group to come up with cohesive decisions.”

The starting point for this research is artificial neural networks, which McCulloch and Pitts pioneered in 1943 by creating a computational model for neural networks based on mathematics and algorithms. Much of the early research into artificial neural networks focused on mapping and understanding the electrical activity of neural networks. Dr. Thanga’s research builds on this by trying to understand “the interplay between electrical and chemical communication between cells.”

The roots of Dr. Thanga’s research lie in Darwinian evolution. Just as farmers used to breed specific traits into animals, “we do the same towards developing robust controllers, particularly in multi-robot systems.” The goal is getting robots to work together cohesively towards solving a task. While the algorithms and science behind the process is quite complex, Dr. Thanga says the process itself is quite simple.

“We define a task, and then set a structure by which accomplishing that can be quantitatively studied; where zero is bad, and one is absolutely brilliant. […] Next, what we have to provide is the library of behaviors that these robots may have access to.”

Some of these behaviors may be useful, and others may not, but they represent all the behaviors the robots have access to. A library of sensory inputs is also provided to the robots, in addition to a library of training scenarios. “We provide this whole mixture of ‘things’ and then let the controllers be selected from this evolutionary process.” Over many generations, the robots that are able to “make a dent” in solving the task are allowed to metaphorically reproduce towards the eventual goal of solving the task.

When it comes to solving these tasks, Dr. Thanga has discovered that there is not one “right” solution. “There is a spectrum of solutions between good and brilliant.” This is where neural networks are especially valuable. “Neural networks are generalized. If you don’t know what function you need to use to solve a task, a neural network can adapt to solve a task.”

A second important characteristic of Dr. Thanga’s research is task decomposition. Says Thanga, “that’s something that we as humans learn right through our life. It’s our basic life process, taking some complex task that we don’t know how to solve, breaking it up into smaller and smaller chunks, solving the smaller tasks, and then using those solutions to solve the ‘grand’ task.” With evolutionary robotic systems, Dr. Thanga is “teaching” robots to approach problem solving like biological organisms would. While the research takes place in a virtual environment, the results can be programmed into physical robots.

The application of this research in the real world is potentially massive. Dr. Thanga’s current focus is training robots to excavate and build real world structures like landing strips, or building the foundations of buildings. The advantage of using multiple robots to accomplish a task as opposed to a single robot lies in, “using multiple imperfect individuals working together to accomplish a task, as opposed to needing one perfect individual to accomplish the task.”

Using many “imperfect” robots as opposed to one “perfect” robot lowers costs and allows for automation of complex tasks such as installing and maintaining solar farms, mining, construction, and other industrial tasks. Modeling the robots on biological neural systems grants them the ability to adapt to changing conditions just as humans do. And as Dr. Thanga’s virtual robots are translated into the physical world, opportunities for accomplishing tasks in environments not suited for humans becomes more of a reality.

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The team, comprised of Daniela Rus, Professor of Electrical Engineering and Computer Science and Director of CSAIL, Cagdas Onal, Assistant Professor of Mechanical Engineering at the Worcester Polytechnic Institute, and Andrew Marchese, a doctoral candidate in engineering at MIT, created the robot to be autonomous. This means it has all the necessary sensing, actuation and computation on board. Its flexible body is made of silicone rubber. The robot fish is able to swish from side to side as onboard gas inflates and deflates different parts of its body. This means that the robot is flexible and can maneuver like a real fish—making a full C-turn with its body in just 100 milliseconds.

According to Rus, this type of soft robot is inherently safe, saying “As robots penetrate the physical world and start interacting with people more and more, it’s much easier to make robots safe if their bodies are so wonderfully soft that there’s no danger if they whack you.”

The fish can perform 20-30 agile escape maneuvers before its carbon dioxide canister runs out. The team is working on an updated version that will be able to swim for around 30 minutes using water to inflate its interior channels rather than carbon dioxide.

In the not so distant future, the fish-bot could be put to use for covert science missions where it might be able to infiltrate schools of real fish to collect data about their behavior.  

The field of soft robotics holds great potential for the development of smart machines that can adjust their shape and size to fit variable environments and interact with living things without causing them harm. Possible applications include: mine detection, assistive healthcare, search and rescue missions and space instrument repair.

António Câmara is a man with a vision.

Despite the widespread adoption of computers and digital technology over the last few decades, how we interact with that technology, and use technology to interact with the world around us has remained largely unchanged. For example, for over 30 years, the primary means of interacting with a computer has been the keyboard and mouse. Certainly there have been updates to the technology – trackpads, for example, have become a popular mouse alternative – but that essential method of interaction remains the same. Even touch screens, perhaps the most widespread change in how people interact with technology, date back to the 1980’s.

However, the widespread adoption and increasing power of smartphones has opened up exciting opportunities for emerging technology; opportunities that Câmara’s company YDreams is exploring. Since its founding in 2000, YDreams has been involved in advancing mobile phone technology. It developed the first location-based games with a visual interface and continues to explore the new possibilities for human-computer interaction, augmented reality and robotics that smartphone technology supplies.

YDreams may be based in Portugal, but the company is distinctly involved in the American technology scene. Since one of YDreams’ main goals is to function as an incubator, it has formed strategic partnerships with several American companies and startups. This distributed business model allows it to support emergent technology and pursue multiple avenues of research simultaneously. Much of that research is currently focused on advancing the field of robotics.

Towards that end, its robotics initiatives are separated into two distinct focus areas: robotics for use in urban environments, and robotics for oceanic exploration. Their Santander Siga project utilizes swarm robotics to create a fleet of “robotic butlers” to guide and interact with visitors to the massive 0.6 square-mile Ciudad Grupo Santander complex. But Santander was only the beginning for YDreams.

Last year, its Ziphius aquatic drone was successfully funded on Kickstarter and garnering high praise from industry insiders. The football-sized aquatic drone can be controlled from an android-powered smartphone or tablet, features an HD camera, and can reach speeds of up to 5.4 Knots. The Raspberry Pi powered Ziphius is targeted at both scientific and consumer markets. The drone can play catch, features augmented reality games, and yet also has scientific uses like marine exploration and environmental monitoring.

The Ziphius drone characterizes how Câmara and YDreams are using robotics to change how we interact with the world around us. And still, this is only the tip of the iceberg. Câmara hopes to change the way people think about home robotics, a field which has been characterized by toys and the Roomba for over half a decade.

According to Câmara, “The next generation of robots will use a smartphone as a brain.” The first of Câmara’s home robotics innovations is an object found in almost every home, the lamp. The robotic lamp, which will be controlled from a smartphone, will be able to react intelligently to lighting conditions and human input. This melding of robotic innovation and common household objects opens the doors for a whole generation of “invisible devices,” says Câmara.

“The functions of these robots will be helpful and entertaining, but you won’t see the robots themselves. You will be able to interact with them in the home environment in a truly ubiquitous computing way. The processors and displays will blend with the home environment.”

Taking an object that people already regularly interact with and giving it “intelligence” might seem like the stuff of science fiction, but the key is the smartphone itself says Câmara. “Smartphones already have intelligence, sensors, and communication capabilities. Basically, most of what you need for a robot is already in a smartphone.”

Rather than attempting to radically re-invent core robotic systems, researchers like Câmara are leveraging the billions of dollars poured into smartphone technology, creating robotics platforms built around the technology that’s already in use. Since the smartphone provides the core “intelligence” for robotics applications, it allows the robots themselves to be much cheaper, opening up avenues for consumer robotics applications that would have been financially impossible before smartphones. Also, widespread smartphone ownership will aid user adoption of new robotic applications, since the central control unit is a device already in use.

Changing the way people interact with their home environments through the use of distributed computing and interactive technology creates numerous opportunities for entrepreneurs, says Câmara. Opportunities for improving human interaction with the world through the use of technology is still in its infancy, but Câmara believes that technology like 3D printing will allow startups to develop robotic applications that would have been otherwise cost prohibitive. With the avenues that smartphones and 3D printing are opening, the question a startup should ask is, “how can I interact with my world better?”

NASA came up with the answer recently when their teams began putting one of its humanoid robots through medical school. Should a medical incident arise in space that human crew members are unable to deal with themselves, the robo-doc will be there to save the day. Once trained, the robot doctor should be able to complete basic medical procedures unassisted. For more complicated procedures, an earth-based physician could control the robot via telepresence.

After its training is complete, the $2.5 million Robonaut 2, designed to assist astronauts with their duties both inside and outside the International Space Station, will be able to add medical practices to its resume.

Medical training is a complex and lengthy process, even for a robot. Unfortunately there is no super-software that can be uploaded to the robot to make it become an instant medical expert. But one of R2′s instructors, Dr. Zsolt Garami, M.D. says that the robot is a quick learner; in one hour it can pick up as much as it takes human medical student one week to learn.

R2 joined its mechanical twin Robonaut 1 aboard the International Space Station on August 22, 2013. Unlike R1, which is just a head and torso, R2 has been given motorized legs and is much more dexterous. Software may be upgraded in the future to allow R2 to move around the stations interior and perform routine maintenance tasks such as cleaning filters. Other upgrades may enable the robot to work outside the space station to perform repairs and maintenance checks when there is no call for medical assistance.

In the not too distant future, robotic doctors could be beneficial for patients here on earth where they could perform telesurgery in remote areas or where specialist surgeons are not available. It’s also reassuring to know that by the time humans are ready to colonize Mars, Robonaut doctors will be there to lend a healing hand.

A paper in Nature Communications earlier this year reports on “bio-bots”. These tiny machines inspired by sperm, are a hybrid combination of live heart cells and a synthetic polymer body.

The new bots, developed by researchers from the University of Illinois and Arizona State University, are the first swimming micro-machines that mimic the flagellar movement of sperm to traverse the viscous fluids of biological environments. This means they can propel themselves onward, fired by the contractile power of heart cells. The bio-bots are just 2 millimeters long and basically consist of a head and a wire tail with the some live cells to make it functional. The small cluster of heart cells are grown at the intersection of the head and the tail. They are synchronized to beat together, creating a wave motion in the tail that can push the bot forward at a speed of up to 10 micrometers per second.

The bio-bot’s creators have also designed a similar micro-bot with two tails that can swim even faster; up to 81 micrometers per second. According to the team’s lead investigator, Taher Saif, this type of robotic phenomena is the first of its kind, and the team is not quite sure how the cells communicate to synchronize their movement. Saif explained that the additional tail allows the bio-bots to navigate. He predicts that future applications could include: chemical detection, light sensing or they could be programmed to reach a specific target for medical or environmental purposes.

While there is still much work to be done, this program marks the innovative first step towards a new realm of bio-hybrid machines. Saif teamed up with fellow University of Illinois researchers Brian J. Williams and Sandeep V. Anand, as well as Arizona State University’s Jagannathan Rajagopalan. Their work was completed as part of Emergent Behaviors in Integrated Cellular Systems (EBICS), a National Science Foundation-funded Science and Technology Center.

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Jessica Feldman is a neuroscientist and PHD student at Brown University who is working with, among other projects, the BrainGate Group. BrainGate is a team of neurologists, neuroscientists, and other researchers all working towards a single goal: developing technologies that will restore the communication, mobility, and independence of people with neurological disease, injury, or limb loss.

The common term for this type of emerging technology is “brain-computer interfaces” (BCI), and it has the potential to change how we all interact with technology and the world around us at the most basic levels. Research into BCI began in the 1970s at UCLA under a grant from the National Science Foundation, and later DARPA. While research was initially limited to animals, the first human neuroprosthetic devices were implanted in the mid 1990s.

One of the largest barriers to effective BCI is translating neural activity into an effective machine signal, e.g., “telling” a robot arm to move in response to neural activity. Advances in methods of recording neural activity such as EEG and ECOG have improved this technology somewhat, but it’s still a very unnatural process. The goal of BrainGate and researchers like Feldman is to create natural “biomimetic” interfaces. Basically, thinking about picking up a glass of water would cause the machine to complete the complex collection of actions to pick up a glass of water.

The key to unlocking this type of interface lies with intracortical electrodes, says Feldman. These tiny wires are implanted in the brain’s cortex, and allow a single neuron’s activity to be recorded and mapped. Using a group of these wires, and taking up less than the space of a penny, allows researchers to record more complex signals.

This advance in recording neural activity opens up new avenues for helping individuals who are paralyzed or have lost a limb. Essentially, the signal of thinking about moving a lost limb can be sent to a prosthetic, causing the prosthetic limb to move. It’s an incredibly complex process, requiring specific hardware, processors, and technology. But the core necessity remains decoding the natural brain activity involved in any and every action. Says Feldman, “There’s so much basic science that goes on, even the smallest of neurophysiological questions are things that we’re looking at every day.”

However, the potential rewards are worth the effort, and “huge strides are being made,” says Feldman. The BrainGate neural device (currently in FDA human trials) has assisted individuals suffering from spinal cord injury, brainstem stroke, and ALS. At this stage, it allows individuals to control a computer cursor by thinking about the movement of their own paralyzed hand, or to use a mechanical arm to pick up and sip from a coffee cup simply by thinking about doing it. Since the technology involves physically implanting wires into the human brain, issues of safety and the longevity of the device must be thoroughly addressed. This is the BrainGate team’s next goal so that the device can move beyond the research stages.

The ultimate goal, says Feldman, “is to have a product that is an assistive medical device that can be used by any person with paralysis,” that can “restore their mobility and independence.” While the components are bulky now, as the technology continues to develop, miniaturization becomes more and more feasible. The BrainGate team currently is working on creating an autonomous system that is capable of wireless transfer. Feldman says that the aim is to create a device that can wirelessly communicate with a control unit that is small enough to be carried in a person’s pocket.

The current research and technology is focused on restoring mobility and independence to paralyzed individuals, but the potential applications are virtually unlimited. Decoding the signals of the brain and analyzing brain patterns opens up avenues for epilepsy research, artificial limbs, and understanding neurological diseases. Says Feldman, “at a basic neuroscience level, we’re learning about brain circuitry, neural circuitry, how things work. We’re able to study how the brain works for the first time at the micro level.” The real discovery in BrainGate’s research is how cognition becomes behavior.

In the end, the question isn’t what the implications of this research could be, but is there any area of human life that this technology would not effect?

Camilleri and his team have been studying brain responses for ten years. Now they have found one that is optimal for controlling a music player using eye movements. The system was originally developed to improve the quality of life of individuals with severely impaired motor abilities such as those with motor neuron disease or cerebral palsy.

The technology works by reading two key features of the user’s nervous system: the nerves that trigger muscular movement in the eyes and the way that the brain processes vision. The user can control the music player simply by looking at a series of flickering boxes on a computer screen. Each of the lights flicker at a certain frequency and as the user looks at them their brain synchronizes at the same rate. This brain pattern reading system, developed by Rosanne Zerafa relies on a system involving Steady State Visually Evoked potentials (SSVEPs).

Electrical signals sent by the brain are then picked up by a series of electrodes placed at specific locations on the user’s scalp. This process, known as electroencephalography (EEG), records the brain responses and converts the brain activity into a series of computer commands.

As the user looks at the boxes on the screen, the computer program is able to figure out the commands, allowing the music player to be controlled without the need of any physical movement. In order to adjust the volume, or change the song, the user just has to look at the corresponding box. The command takes effect in just seconds.

For people who have become paralyzed due to a spinal injury, the normal flow of brain signals through the spine and to muscles is disrupted. However, the cranial nerves are separate and link directly from the brain to certain areas of the body, bypassing the spine altogether. This particular brain-computer interface exploits one of these; the occulomotor nerve, which is responsible for the eye’s movements. This means that even an individual with complete body paralysis can still move their eyes over images on a screen.

This cutting age brain-computer interface system could lead the way for the development of similar user interfaces for tablets and smart phones. The concept could also be designed to aid with assisted living applications, for example.

The BCI system was presented at the 6th International IEEE/EMBS Neural Engineering Conference in San Diego, California by team member Dr. Owen Falzon.

PackBots will be deployed in Brazil during the 2014 World Cup Soccer season to bring a high-tech approach to security. The nation’s government has secured a $7.2 million deal with PackBot’s creators for 30 of the military bots. The robots will be stationed throughout Brazil’s 12 host cities, during the soccer matches to boost security and help examine any suspicious objects.

The sleek PackBot robot system, designed by iRobot, a Bedford, Massachusetts-based company, made its debut in 2002 in Afghanistan, where it helped soldiers clear bunkers, caves, collapsed building and to cross minefields. The versatile machine was used again in 2003 in Iraq in urban warfare situations and to search vehicles. By 2007, more than 800 of these military robots were in use throughout Afghanistan, Iraq and several other countries. The PackBot was also the first remote controlled robot to enter the Fukushima nuclear facility after the East Japan Earthquake and tsunami in March 2011.

PackBot is a unique robotic propulsion system that can reach a road speed of up to 9 miles/hour. The bot’s in-built flippers allow it 360 degrees of rotation, enabling it to negotiate rough terrain and even obstacles like logs, rocks, rubble and stairs. PackBot has the capability to climb up to 60 percent grades and survive submersion in water up to two meters depth.

Its robust body can survive a fall from a two meter height to a concrete surface, being flung through a window and falling downstairs. This bot weight less than 40lbs, and is easily carried in a back pack, ready to be deployed within minutes.

PackBot’s other attributes include a state-of-the-art GPS, video image display, system monitoring, electronic compass, temperature sensors. The robot is manipulated with an integrated Pentium-based computer.

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What has the capability to strengthen homeland security, produce a ball’s-eye view of a soccer match and swim underwater with dolphins? GuardBot: the latest development in unmanned amphibious vehicle systems.

The cutting-edge spherical robot was developed by Connecticut-based American Unmanned Systems. The 54-pound bot can roll over the roughest terrain including snow, mud, rocks and sand and is the only unmanned amphibious device that is capable of navigating through water. Its motion drive system is operated by an internal battery-powered pendulum that can operate for up to eight hours on one charge. The mechanism propels the ball by shifting the center of gravity, allowing back and forth movements and 360° turns. GuardBot can maintain speeds of 6 mph on land and 3 mph in water.

You can see the bot in action in this video from Reuters:

Originally designed in 2004 to rove across the Martian terrain for a European Space Agency mission, GuardBot is currently being used for military and commercial applications. Its main tasks are guard and reconnaissance duty and rescue missions. Moving in virtual silence, the robot sentry can be programmed to operate by GPS or remotely controlled by an operator, permitting unobtrusive surveillance as well as inspection and identification of surrounding areas and objects.

GuardBot is undergoing tests by the Marines in Quantico, Va., and Camp LeJeune, N.C. Its commercial applications include dolphin research at an aquarium in Florida and a recent deployment during a live soccer match at Mexico City’s Azteca Stadium.

GuardBot Inc. is currently working to enhance the device’s systems by improving control, extending battery life and adding radiation detectors, imaging devices, advanced radios, and sonars.

Artificial intelligence has it’s advantages. Systematically, over decades of research and development, AI has come to dominate human intelligence in a number of specific and often limited tasks. Yet, AI – at least thus far – has still lagged human intelligence in certain types of rich pattern recognition. For example, AI programs are still comparatively inept with regards to picking up and handling different kinds of objects, and until recently, AI seemed to struggle vehemently in discerning a “cat” from a “dog” on a screen (see: Kaggle).

Today, the human brain has the capacity to recognize and make sense of patterns in ways that AI’s cannot, an ability that was famously pooled in “crowd-sourced intelligence” in “Fold.it,” a game created in the University of Washington. The concept is this: Take thousands of human brains, use them to solve complex problems of protein-folding, allowing scientists who work with the game to create better medications with new protein possibilities, and to adjust the algorithms for their present protein-folding software.

Ivo Georgiev, CEO at Proteo.me, is aiming to take gamification in a new direction. He told me “Fold.it is more specifically targeted to learning how proteins of a certain sequence can fold in on themselves – what we’re doing [at Proteo.me] is more about optimizing already known proteins for novel uses.” Ivo’s team aims to keep the folds of known proteins, and tuning them to bind or interact in specific ways (IE: to help create a drug or treat a condition). In addition, Ivo plans to piggy-back on what he calls the “explosion in mobile gaming” (not a bad assessment) by making his game mobile from the get-go.

Ivo sees this “gamification” as a trend that may enter many other aspects of our lives. He first references the fact that multiple human beings can often discover unique and otherwise unknown opportunities for problem-solving in nearly any field (with Fold.it being a prime example). In addition he references the fact that a group of humans – even in disagreement – are often better at discerning a solution than any one particular person (see: The Wisdom of Crowds).

Ivo mentions “the name [gamification] itself is going to go out of vogue, but as more and more project become involved and figure out how to do well in their own fields, this will become the norm rather than the exception.” In a world permeated by “big data,” it doesn’t seem unreasonable to suspect that – so long as we’re still smarter than machines – our own individual insights might not be pooled and collected (potentially in ways that are still entertaining – like “fold.it”).

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Why do people who use Facebook spend so much of their online time there? Why do people want to share, to comment?
Patrick Levy Rosenthal asked himself these answers and was drawn back again and again to: Emotion. Researcher and Parisian, Patrick now lives in London working on his startup, EmoSpace.

Over the course of our conversation, he painted a bit of his vision for an emotionally attuned physical world, where objects and devices around us can adjust their function to have a desirable effect on our emotional state, or to simply “sync” with us at an emotional level. I spoke a bit about this same topic with RockPaperRobot’s Jessica Banks, but Patrick’s business concept – and life’s work – is creating the first user interface for emotionally calibrating devices. It starts with a small cube-shaped object “EmoSPARK,” which Patrick plans to have fitted with the technology to connect to a number of other household devices – beginning (most likely) with an mp3 music player.

The first question is: How will this machine detect it’s owner’s emotional state?

Patrick explains that this should be one of the simpler challenges of the device. “It tracks over 180 points on your face, but also the relation between those points, so that if you are smiling it will know that your lips will be stretched, and eyes made more narrow.” The machine will also be able to detect movement and voice tonality in order discern the emotional state of it’s owner.

In terms of the application of this data, Patrick started with the example of tying the emotional feedback to a basic music device. If you walk into a a room and display plenty of signals of sadness (slumped shoulders, low voice tones, frown), the machine will aim to bring your emotion up another level via a piece of music that might bump your emotional state upwards. In doing so, the machine will aim to detect the effect that the music is having on your emotions, or the machine may simply ask you if you like the music, or what you’re in the mood for. In doing so, it can remember your responses to certain stimuli, and remember which stimuli tended to be most helpful for you in which situations, and so perform it’s job (improving your state / creating a desirable environment) better day by day. Patrick’s vision is for lighting, computers, and myriad other devices to have a similar kind of resonation with your emotions by attaching them to the cube.

“For the last 20 years, I believe that robotics and artificial intelligence failed humans.” He admits that in many respects, robots are impressive in their modern feats, but that they are nowhere near the level of intelligence that many people supposed they might be a few decades ago. ”We still see them as a bunch of silicon… we know that they don’t understand what we feel.” Patrick also mentions the uncanny valley, and how more realistic robots are often more threatening and troubling than ones which do not look like humans, and how a machine like Disney’s WALL-E appeals to us because it is not humanoid (read: creepy), and because WALL-E is clearly an emotional creature.

I asked Patrick a bit about the potential risks for an emotionally intelligent machine. It would seem that a machine which is capable of experiencing emotion itself might be capable of doing what humans do when they get emotional. Namely: rash things, violent things, irrational or unpredictable things. Patrick explained that he will have laws programmed into his machines which do not permit them to – say – harm humans, or act with any kind of malicious intent (for those of you who are interested, his rules are modeled and extrapolated from Asimov’s robot lows). “Even if you hurt the feelings of the cube, it will always gear it’s actions towards making you feel better,” he says.

In the end, Patrick believes that emotional intelligence in machines will – on the aggregate – make us less likely to run into a “Terminator” situation in the future. For his sake and mine, I hope so, too.

First, I asked him to give me an idea of the “state of robotics” at the present time – so that I might grasp where the field is today compared to where things were be even 5 or 6 years ago. Tjin refers to the fact that after an initially slow past decade in robotics, he’s seen a lot of progress over just the last half-decade, which for him seems promising. “We went from robots that couldn’t play soccer (the traditional competitive activity of Robocup)… were unlikely to be used at home… to robots that can open the fridge, get a beer, open the beer for you, and bring it to you.” He’s seen everything from robots flipping pancakes to serving drinks at bars – and the variety and complexity of these tasks increases noticeably year-after-year at Robocup.

What has enabled this transition? A number of congergent factors have come together to help take robotics to the point that it’s reached today. First and foremost, says Tjin, the X-box “Kinect” and mobile phone companies have given robotics teams in and out of academia a series of cheap and highly effective sensors that would have cost the teams years of time and millions of dollars to create themselves.

In addition, with many of the Robocup competitors being from universities, the purpose of competition is the growth and development of the field – allowing open-source robotics software to be developed, and more useful skills to be shared among the brightest and most eager minds in the field. The result? Tjin reports that teams in remote and unknown areas can often come into Robocup competitions and do just as well as the better-known schools, because they have software and knowledge access that now rivals anywhere else in the world. Robocup itself is intending to facilitate these developments, and by bringing robotic teams together head-to-head, the field is furthered by real, competitive aims (rather than merely new or novel innovations). A set of rules, a bunch of excited scientists of all ages, and a clear objective means a lot of specific learning for everyone involved.

As for the future of robotics, Tjin shared some insights that I had never heard from any of my other interviewees. “I would not be surprised that if in 30 years there were several robots per person, with specialized tasks. This means there will be a huge commercial applications… and these robots would have to adjust differently for different cultures.” He admits that he’s prognosticating, but he sincerely feels that the cultural differences between us will be manifested in the robots around us (much like McDonalds offering different foods in different cultures). He uses the humorous example of a more design-focused country like Italy which wants its sewage-cleaning robots to look good – despite their job.

In addition, different countries and cultures may have different ideas about what a robot should be or do. “In Japan, people see robots as a friend, they want a robot buddy. In northwestern Europe… nobody really cares about this… because we want to robots to do the tasks that we don’t want to do, or which are too dirty.”

One of the biggest areas where Tjin feels that robotics will have home applications is with elderly communities. He mentioned that the percentage of the elderly population is on the rise and that it will be unreasonable to hire individual around-the-clock helpers to care for the elderly – and that it may be a job perfectly suited for a robot which can provide telepresence capacities for loved ones to “visit” the elderly, as well as remind elderly individuals to take medication, or to notify neighbors when an accident or fall happens. Tjin’s own startup in the robotics world (Assistobot) is geared towards serving elderly individuals in managed care facilities and hospitals, a body of work that he – and the teams of talented researchers at the Robocup events – will continue working on.