Bionics  

Researchers at MIT have developed a device, worn around the wrist, that enhances the grasping motion of the human hand with two robotic fingers.

Researchers at MIT have developed a robot that enhances the grasping motion of the human hand. Like another recent project at the university that gives the user an extra set of arms, the new wrist-mounted robot can help you twist a screwdriver, remove a bottle cap, and peel a banana single-handedly.

The device, worn around one’s wrist, works like two extra fingers adjacent to the pinky and thumb. The device's algorithm enables it to move synchronously with the user’s fingers for grasping objects of various shapes and sizes.

“This is a completely intuitive and natural way to move your robotic fingers,” says Harry Asada, the Ford Professor of Engineering in MIT’s Department of Mechanical Engineering. “You do not need to command the robot, but simply move your fingers naturally. Then the robotic fingers react and assist your fingers.”

"You do not need to command the robot, but simply move your fingers naturally. Then the robotic fingers react and assist your fingers."

Asada says, with some training people may come to perceive the extra bionic fingers as part of their body — “like a tool you have been using for a long time, you feel the robot as an extension of your hand.” He hopes that the two-fingered robot may assist people with limited dexterity in performing routine household tasks, such as opening jars and lifting heavy objects. He and graduate student Faye Wu presented a paper on the robot this week at the Robotics: Science and Systems conference in Berkeley, California.

The robot, which the researchers have dubbed “supernumerary robotic fingers,” consists of actuators linked together to exert forces as strong as those of human fingers during a grasping motion.

To develop an algorithm to coordinate the robotic fingers with a human hand, the researchers first looked to the physiology of hand gestures, learning that a hand’s five fingers are highly coordinated.

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The researchers hypothesized that a similar “biomechanical synergy” may exist not only among the five human fingers, but also among seven. To test the hypothesis, Wu wore a glove outfitted with multiple position-recording sensors, and attached to her wrist via a light brace. She then scavenged the lab for common objects, such as a box of cookies, a soda bottle, and a football.

Wu grasped each object with her hand, then manually positioned the robotic fingers to support the object. She recorded both hand and robotic joint angles multiple times with various objects, then analyzed the data, and found that every grasp could be explained by a combination of two or three general patterns among all seven fingers.

The researchers used this information to develop a control algorithm to correlate the postures of the two robotic fingers with those of the five human fingers. Asada explains that the algorithm essentially “teaches” the robot to assume a certain posture that the human expects the robot to take.

Down the road, Asada says the robot may also be scaled down to a less bulky form. “This is a prototype, but we can shrink it down to one-third its size, and make it foldable,” Asada says. “We could make this into a watch or a bracelet where the fingers pop up, and when the job is done, they come back into the watch. Wearable robots are a way to bring the robot closer to our daily life.”




SOURCE  MIT

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 Artificial Intelligence  

Explaining how intelligence may be an emergent property rooted in the urge to take control of all possible futures, Alex Wissner-Gross has developed an equation that may explain intelligence itself, and in doing so, may dramatically impact the world of AI.

Richard Feynman once wrote that if human civilization were destroyed and you could pass on only a single concept to our descendants to help them rebuild civilization, that concept should be that all matter around us is made out of tiny elements that attract each other when they are far apart, but repel each other when they are close together.

For Alex Wissner-Gross, the equivalent statement to pass on to descendants to help them build artificial intelligence or to help them understand human intelligence is "That it should be viewed as a physical process that tries to maximize future freedom of action and to avoid constraints in its own future."

This grand view of intelligence has emerged as a guiding principle for Wissner-Gross's own work in development of Entropica, an artificial intelligence platform that has been tested for use in robotic motion planning, computer game play and financial market trading maximization.

Wissner-Gross began his work in artificial intelligence by first trying to understand the fundamental physical mechanisms that underlay intelligence.

In a paper published earlier this year, Wissner-Gross detailed how intelligent behavior stems from the impulse to seize control of future events in the environment. This is the exact opposite of the classic science-fiction scenario in which computers or robots become intelligent, then set their sights on taking over the world.

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The work led Wissner-Gross to also develop a single equation to explain intelligence. Wissner-Gross calls it, "the closest thing to an E=MC² for intelligence."  In the equation, F is a force that acts so to maximize future freedom of action, to keep options open with some strength, T with S, an amount of diversity to possible accessible futures, up to some future time horizon, Tau.

In the video above, Wissner-Gross shows how the equation can be applied to artificial intelligence. As the demonstration of Entropica suggests, intelligent behavior doesn't just correlate with the production of long term control of future events, or entropy, it actually emerges from it.

With the equation as a fundamental algorithm, Entropica was able to pass multiple animal intelligence tests, play games and even earn money trading stocks, all without being instructed to do so.

Wissner-Gross is an American scientist, inventor, and entrepreneur. In 2003, he became the last person in MIT history to receive a triple major, with bachelors degrees in physics, electrical engineering, and mathematics, while graduating first in his class from the MIT School of Engineering. In 2007, he completed his Ph.D. in Physics at Harvard, where his research on programmable matter, ubiquitous computing, and machine learning was awarded the Hertz Doctoral Thesis Prize. He currently holds academic appointments as an Institute Fellow at the Harvard University Institute for Applied Computational Science and as a Research Affiliate at the MIT Media Lab.

SOURCE  TEDx Talks

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 Artificial Intelligence  

IBM is working to extend the capabilities of cognitive computing systems like Watson, and is engaging the support of four university research programs to help. The project partners include Carnegie Mellon University, MIT, New York University and the Rensselaer Polytechnic Institute.

Computer maker IBM has announced a collaborative research initiative with four leading universities to advance the development and deployment of cognitive computing systems – systems like IBM Watson that can learn, reason and help human experts make complex decisions involving extraordinary volumes of fast-moving data.

Faculty at the four schools -- Carnegie Mellon University, the Massachusetts Institute of Technology, New York University and Rensselaer Polytechnic Institute -- will study enabling technologies and methods for building a new class of systems that better enable people to interact with Big Data in what IBM has identified as a new era of computing.

"IBM has demonstrated with Watson that cognitive computing is real and delivering value today," said Zachary Lemnios, vice president of strategy for IBM Research. "It is already starting to transform the ways clients navigate big data and is creating new insights in healthcare, how research can be conducted and how companies can support their customers. But much additional research is needed to identify the systems, architectures and process technologies to support a new computing model that enables systems and people to work together across any domain of expertise."

The research initiative was announced at a colloquium held at the Thomas J. Watson Research Center attended by nearly 200 leading academics, IBM clients and IBM researchers to begin a dialog that deepens the understanding of cognitive systems and identifies additional areas of research to pursue. These initial university collaborators will help lay the foundation for a Cognitive Systems Institute that IBM envisions will comprise universities, research institutes and IBM clients.

The initial research topics for exploration so far are:

- MIT - How socio-technical tools and applications can boost the collective performance of moderate-sized groups of humans engaged in collaborative tasks such as decision making. 

- RPI - How advances in processing power, data availability, and algorithmic techniques can enable the practical application of a variety of artificial intelligence techniques. 

- CMU - How systems should be architected to support intelligent, natural interaction with all kinds of information in support of complex human tasks (it follows that this initiative will involve aspects of Carnegie Mellon's advanced robotics research). 

- NYU - How deep learning is impacting many areas of science where automated pattern recognition is essential.

"I believe that cognitive systems technologies will make it possible to connect people and computers in new ways so that--collectively--they can act more intelligently than any person, group, or computer has ever done before," said Thomas Malone, Director of the MIT Center for Collective Intelligence and the Patrick J. McGovern Professor of Management, MIT Sloan School of Management. "I am excited to be working with IBM and these other universities to understand better how to harness these new forms of collective intelligence."

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"With the explosion of information and the advances in semantic data tools, we are excited to participate in this collaboration to bring the best of human and computing capabilities together in this new era of cognitive systems," said Selmer Bringsjord, Professor and Head of the Department of Cognitive Science at Rensselaer Polytechnic Institute.

"The cost-effective creation of cognitive systems for complex analytic tasks will require fundamental advances in the rapid construction, optimization, and constant adaptation of large ensembles of analytic components. Personalized information agents will rapidly adapt and optimize their task performance based on direct interaction with the end user. I am excited that CMU will be teaming with IBM, MIT, RPI and NYU to explore the future of software architecture for cognitive systems," said Eric Nyberg, Professor at the Language Technologies Institute at Carnegie Mellon University.

"NYU's research into neural networks has the potential to revolutionize how we think about machines and the role they play in our everyday lives. NYU has a long history of helping create some of the work's most important technological breakthroughs, so we are honored to be among the universities collaborating on this research initiative into cognitive computing systems," saidPaul Horn, Senior Vice Provost for Research at New York University. "As a research university at the forefront of technology and innovation, we look forward to working with IBM and our fellow institutions to promote basic research into the next era of computing."

SOURCE  IBM

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