The company said a camera that recognises three-dimensional shapes and their movements will combine with a projector that could show the image of an input device -- such as a keyboard -- on almost any surface.

Users can then gesture at the projected image to move an electronic file or play a video, with the movement of their hand relayed back to the device they want to control.

"With the recent expansion of cloud-based services, information terminals have become increasingly diversified, ranging from PCs to smartphones and tablet devices," a company statement said Tuesday.

"However, the presentation of information is limited to the displays on such devices, and operation needs to be performed with the use of an input device such as a remote control, mouse or touchscreen.

"Using this technology, multiple devices can be controlled based on a user's movements, without the use of an input device, producing interfaces that boast more natural interaction."

NEC said it hoped to develop the technology so that it could be used with devices that do not have displays, including lights and air conditioners, raising the prospect of a home controlled largely by waving.

]]> Thu, 17 MAY 2012 17:52:27 AEST Worcester, MA (SPX) May 14, 2012 - Autonomous robots created by 11 teams of engineers from across the country will compete for a NASA prize purse of $1.5 million on the campus of Worcester Polytechnic Institute (WPI), in Worcester, Mass., June 14 -17. The challenge: design and develop the next generation of robots to explore the landscapes of other worlds.

The NASA-WPI Sample Return Robot Challenge requires the competing teams to design and build an autonomous robotic system that will locate and collect a set of specific objects from a large area and return the "planetary samples" to the starting zone.

The innovative technologies the teams bring forward can help NASA in future exploration of distant planets while also potentially benefiting life here on Earth. Earthly benefits could include areas such as disaster recovery and mitigation and remote exploration and mapping of hazardous terrains.

The NASA-WPI Sample Return Robot goals are to discover innovative new technologies to advance robot navigation and sample collection without human control, and demonstrate robotic transportation over varied terrain without the aid of GPS or other Earth-based systems.

The competition also will empower educators and people of all ages by introducing robotics and how they work, where they work, and real-world applications of how robots will be used the future.

The competition's roving area includes open rolling terrain, soft soils, a variety of rocks and immovable obstacles such as trees, large rocks and water hazards. Teams will be given maps with appropriate orbital resolution, including the location of the starting position and a pre-cached sample, but will have no control of the robots during the competition.

Robots will have to identify and collect samples and return them to their starting point. Samples will have different point values. Prizes will be determined based on the scores for the number and point value of samples collected and returned to the starting location.

During the first phase of the competition, a robot must autonomously navigate and retrieve a pre-cached sample within 15minutes. Teams will compete for portions of a $50,000 total prize purse, with a maximum winning value of $5,000 per team.

In the second phase, a robot must autonomously navigate and retrieve pre-cached samples as well as other, more difficult samples distributed over the roving area within two hours. Teams will compete for up to $1.5 million during this phase, with awards depending on the amount of points scored and number of successful competing finalists.

WPI is the first university selected as host and manager for one of NASA's Centennial Challenges Programs, which promotes technical innovation through novel prize competitions.

NASA chose WPI to run this Centennial Challenge because of its proven experience managing robotics competitions, its academic expertise in robotics engineering, and its leadership in science, technology, engineering and mathematic education.

NASA uses prize competitions to establish important technical challenges without having to specify the approach that is most likely to succeed, while only paying for successful results.

These competitions increase the number and diversity of individuals, organizations and teams that are addressing a particular problem or challenge of national or international significance. These challenges stimulate private sector investment many times greater than the cash value of the prize.

]]> Thu, 17 MAY 2012 17:52:27 AEST Tokyo (AFP) May 8, 2012 - Japanese electronics giant Sharp said Tuesday it had created a robot vacuum cleaner capable of recognising and responding to simple voice commands in several languages.

The Cocorobo understands dozens of phrases such as "good morning", "clean the room" and responds differently "depending on the cleaning situation", Sharp said in a statement.

It will also update owners on the battery level, when the dust collector needs emptying and such and even has a camera to take snaps of areas that need cleaning.

The robot speaks standard Japanese as well as English, Chinese and western Japan's Kansai dialect, used in areas around the city of Osaka where Sharp is based, the company said.

The company did not give the price of the new cleaner, which it will start selling in June, but Kyodo news agency said the model equipped with conversation and camera functions is to sell for about 130,000 yen ($1,630).

]]> Thu, 17 MAY 2012 17:52:27 AEST Atlanta GA (SPX) May 08, 2012 - Gaining access to the inner workings of a neuron in the living brain offers a wealth of useful information: its patterns of electrical activity, its shape, even a profile of which genes are turned on at a given moment. However, achieving this entry is such a painstaking task that it is considered an art form; it is so difficult to learn that only a small number of labs in the world practice it.

But that could soon change: Researchers at MIT and the Georgia Institute of Technology have developed a way to automate the process of finding and recording information from neurons in the living brain.

The researchers have shown that a robotic arm guided by a cell-detecting computer algorithm can identify and record from neurons in the living mouse brain with better accuracy and speed than a human experimenter.

The new automated process eliminates the need for months of training and provides long-sought information about living cells' activities. Using this technique, scientists could classify the thousands of different types of cells in the brain, map how they connect to each other, and figure out how diseased cells differ from normal cells.

The project is a collaboration between the labs of Ed Boyden, associate professor of biological engineering and brain and cognitive sciences at MIT, and Craig Forest, an assistant professor in the George W. Woodruff School of Mechanical Engineering at Georgia Tech.

"Our team has been interdisciplinary from the beginning, and this has enabled us to bring the principles of precision machine design to bear upon the study of the living brain," Forest says. His graduate student, Suhasa Kodandaramaiah, spent the past two years as a visiting student at MIT, and is the lead author of the study, which appears in the May 6 issue of Nature Methods.

The method could be particularly useful in studying brain disorders such as schizophrenia, Parkinson's disease, autism and epilepsy, Boyden says. "In all these cases, a molecular description of a cell that is integrated with [its] electrical and circuit properties ... has remained elusive," says Boyden, who is a member of MIT's Media Lab and McGovern Institute for Brain Research.

"If we could really describe how diseases change molecules in specific cells within the living brain, it might enable better drug targets to be found."

Kodandaramaiah, Boyden and Forest set out to automate a 30-year-old technique known as whole-cell patch clamping, which involves bringing a tiny hollow glass pipette in contact with the cell membrane of a neuron, then opening up a small pore in the membrane to record the electrical activity within the cell. This skill usually takes a graduate student or postdoc several months to learn.

Kodandaramaiah spent about four months learning the manual patch-clamp technique, giving him an appreciation for its difficulty. "When I got reasonably good at it, I could sense that even though it is an art form, it can be reduced to a set of stereotyped tasks and decisions that could be executed by a robot," he says.

To that end, Kodandaramaiah and his colleagues built a robotic arm that lowers a glass pipette into the brain of an anesthetized mouse with micrometer accuracy.

As it moves, the pipette monitors a property called electrical impedance - a measure of how difficult it is for electricity to flow out of the pipette. If there are no cells around, electricity flows and impedance is low. When the tip hits a cell, electricity can't flow as well and impedance goes up.

The pipette takes two-micrometer steps, measuring impedance 10 times per second. Once it detects a cell, it can stop instantly, preventing it from poking through the membrane. "This is something a robot can do that a human can't," Boyden says.

Once the pipette finds a cell, it applies suction to form a seal with the cell's membrane. Then, the electrode can break through the membrane to record the cell's internal electrical activity. The robotic system can detect cells with 90 percent accuracy, and establish a connection with the detected cells about 40 percent of the time.

The researchers also showed that their method can be used to determine the shape of the cell by injecting a dye; they are now working on extracting a cell's contents to read its genetic profile.

Development of the new technology was funded primarily by the National Institutes of Health, the National Science Foundation and the MIT Media Lab.

The researchers recently created a startup company, Neuromatic Devices, to commercialize the device.

The researchers are now working on scaling up the number of electrodes so they can record from multiple neurons at a time, potentially allowing them to determine how different parts of the brain are connected.

They are also working with collaborators to start classifying the thousands of types of neurons found in the brain. This "parts list" for the brain would identify neurons not only by their shape - which is the most common means of classification - but also by their electrical activity and genetic profile.

"If you really want to know what a neuron is, you can look at the shape, and you can look at how it fires. Then, if you pull out the genetic information, you can really know what's going on," Forest says. "Now you know everything. That's the whole picture."

Boyden says he believes this is just the beginning of using robotics in neuroscience to study living animals. A robot like this could potentially be used to infuse drugs at targeted points in the brain, or to deliver gene therapy vectors.

He hopes it will also inspire neuroscientists to pursue other kinds of robotic automation - such as in optogenetics, the use of light to perturb targeted neural circuits and determine the causal role that neurons play in brain functions.

Neuroscience is one of the few areas of biology in which robots have yet to make a big impact, Boyden says.

"The genome project was done by humans and a giant set of robots that would do all the genome sequencing. In directed evolution or in synthetic biology, robots do a lot of the molecular biology," he says. "In other parts of biology, robots are essential."

Other co-authors include MIT grad student Giovanni Talei Franzesi and MIT postdoc Brian Y. Chow.

]]> Thu, 17 MAY 2012 17:52:27 AEST San Diego CA (SPX) May 07, 2012 - Can a computer be taught to automatically label every song on the Internet using sets of examples provided by unpaid music fans? University of California, San Diego engineers have found that the answer is yes, and the results are as accurate as using paid music experts to provide the examples, saving considerable time and money.

In results published in the April 24 issue of the Proceedings of the National Academy of Sciences, the researchers report that their solution, called "game-powered machine learning," would enable music lovers to search every song on the web well beyond popular hits, with a simple text search using key words like "funky" or "spooky electronica."

Searching for specific multimedia content, including music, is a challenge because of the need to use text to search images, video and audio. The researchers, led by Gert Lanckriet, a professor of electrical engineering at the UC San Diego Jacobs School of Engineering, hope to create a text-based multimedia search engine that will make it far easier to access the explosion of multimedia content online.

That's because humans working round the clock labeling songs with descriptive text could never keep up with the volume of content being uploaded to the Internet. For example, YouTube users upload 60 hours of video content per minute, according to the company.

In Lanckriet's solution, computers study the examples of music that have been provided by the music fans and labeled in categories such as "romantic," "jazz," "saxophone," or "happy."

The computer then analyzes waveforms of recorded songs in these categories looking for acoustic patterns common to each. It can then automatically label millions of songs by recognizing these patterns.

Training computers in this way is referred to as machine learning. "Game-powered" refers to the millions of people who are already online that Lanckriet's team is enticing to provide the sets of examples by labeling music through a Facebook-based online game called Herd It.

"This is a very promising mechanism to address large-scale music search in the future," said Lanckriet, whose research earned him a spot on MIT Technology Review's list of the world's top young innovators in 2011.

Another significant finding in the paper is that the machine can use what it has learned to design new games that elicit the most effective training data from the humans in the loop.

"The question is if you have only extracted a little bit of knowledge from people and you only have a rudimentary machine learning system, can the computer use that rudimentary version to determine the most effective next questions to ask the people?" said Lanckriet. "It's like a baby. You teach it a little bit and the baby comes back and asks more questions."

For example, the machine may be great at recognizing the music patterns in rock music but struggle with jazz. In that case, it might ask for more examples of jazz music to study.

It's the active feedback loop that combines human knowledge about music and the scalability of automated music tagging through machine learning that makes "Google for music" a real possibility.

Although human knowledge about music is essential to the process, Lanckriet's solution requires relatively little human effort to achieve great gains. Through the active feedback loop, the computer automatically creates new Herd It games to collect the specific human input it needs to most effectively improve the auto-tagging algorithms, said Lanckriet.

The game goes well beyond the two primary methods of categorizing music used today: paying experts in music theory to analyze songs - the method used by Internet radio sites like Pandora - and collaborative filtering, which online book and music sellers now use to recommend products by comparing a buyer's past purchases with those of people who made similar choices.

Both methods are effective up to a point. But paid music experts are expensive and can't possibly keep up with the vast expanse of music available online. Pandora has just 900,000 songs in its catalog after 12 years in operation. Meanwhile, collaborative filtering only really works with books and music that are already popular and selling well.

The big picture: Personalized radio
Lanckriet foresees a time when - thanks to this massive database of cataloged music - cell phone sensors will track the activities and moods of individual cell phone users and use that data to provide a personalized radio service - the kind that matches music to one's activity and mood, without repeating the same songs over and over again.

"What I would like long-term is just one single radio station that starts in the morning and it adapts to you throughout the day. By that I mean the user doesn't have to tell the system, "Hey, it's afternoon now, I prefer to listen to hip hop in the afternoon. The system knows because it has learned the cell phone user's preferences."

This kind of personalized cell phone radio can only be made possible if the cell phone has a large database of accurately labeled songs from which to choose.

That's where efforts to develop a music search engine are ultimately heading. The first step is figuring out how to label all the music online well beyond the most popular hits. As Lanckriet's team demonstrated in PNAS, game-powered machine learning is making that a real possibility.

Lanckriet's research is funded by the National Science Foundation, National Institutes of Health, the Alfred P. Sloan Foundation, Google, Yahoo!, Qualcomm, IBM and eHarmony. You can watch a video about the research and Lanckriet's auto-tagging algorithms to learn more.

]]> Thu, 17 MAY 2012 17:52:27 AEST Paris (ESA) May 08, 2012 - Challenged to design a background for a small rover controlled from space, students in Germany have delivered a futuristic cityscape. The cool space art will be seen by astronauts in orbit via the rover's camera eye as they remotely control their avatar later this year. The ultimate goal is for robot astronauts to roam around hazardous places like Mars and asteroids guided by human controllers safely orbiting overhead in their spacecraft.

As a first step, ESA is linking the International Space Station and Earth for remotely controlling terrestrial test robots from the orbital outpost.

This Meteron (Multi-purpose End-To-End Robotic Operations Network) initiative is a testbed for future missions to the Moon, Mars and other celestial bodies.

Astronauts to practise rover remote control
"Later this year, astronauts on the Station will practise remote control of the small rover in a simulated landscape here at ESOC, says Francois Bosquillon de Frescheville, experiment manager at ESA's European Space Operations Centre, Darmstadt, Germany.

The rover - known as Meteron Operation and CommUnication Prototype, or MOCUP - is built from a LEGO Mindstorm kit with some custom-made additions, and for now can do only simple things.

The astronauts will use a computer on the Station to control the rover and will see what it is 'seeing' and doing on a screen, like a video game.

"The Space Station is the perfect orbital platform to simulate very realistic scenarios for human exploration," says ESA's Kim Nergaard, a Meteron manager.

In the simulation, the rover is meant to be moving through an 'alien' landscape, so the ESA team asked local secondary-school students to design a horizon in the shape of a hexagon built out of 12 painted wooden panels to contain the rover and a number of obstacles for the astronauts to negotiate.

Design open to imagination
"We gave the student team a series of firm technical requirements, but the design of the background was left open to their imagination," says Kim.

"We thought they'd do a reddish, martian desert, maybe with a few boulders. Instead, they delivered a futuristic cityscape.

"It's wonderful, and it speaks volumes about the optimism with which youth imagine the future - it's obviously a pretty cool place."

While brainstorming their graphic design, the 11 students from the Schuldorf Bergstrasse near Darmstadt considered a number of concepts, but finally settled on the cityscape.

"It was a democratic vote by the students themselves, who just thought a future city skyline would be more interesting for the live rover tests," said Petra Thomschke, one of the teachers working with the students.

"Remotely commanding the model rover will provide a through test for the links from the Station to ground, which must be confirmed before moving on to the more sophisticated robots later in the Meteron project," says Kim.

"The students of Schuldorf Bergstrasse can be proud of their contribution to ESA's exploration activities."

]]> Thu, 17 MAY 2012 17:52:27 AEST Washington (UPI) Apr 24, 2012 - Computers may someday help teachers grade their students' essays, and can provide results that mirror human scores, some U.S. educators say.

A wide-ranging study of automated computer essay-scoring software, tested on thousands of sample essays, found a handful of programs "capable of producing scores similar to human scores," USA Today reported.

Computer scoring of essays is a much-debated topic, especially since American students taking SAT college admissions since 2005 have had to write an essay as part of the testing, educators said.

While the National Council of Teachers of English opposes "machine scored" assessments, favoring "direct assessment by human readers," computer-scoring advocates, many of whom are also educators, say the sheer mass of essays being produced by American students cries out for something to help teachers.

Individualized grading by a human reader would be the ideal, Mark Shermis, dean of education at the University of Akron, said, but sheer numbers make that unlikely.

"If every kid in the country had that kind of individualized attention, we might not be having this conversation."

"They really don't understand that most kids are having a hard time communicating at all," he said of those skeptical of machine grading.

Some educators say they're concerned the use of computer grading programs will, in the end, train humans to read more like machines.

"It will get good agreement [between humans and machines] but not necessarily good writing." Les Perelman, director of Writing Across the Curriculum at MIT, said.

Computers should supplement but not replace teachers, Tom Vander Ark of Open Education Solutions, a consulting firm based in Washington State, said.

"I want to see kids writing a lot every day in every classroom across the country and I want teachers, students and parents to have the benefit of more critical feedback," he said. "I want teachers to be able to spend more time on teaching writing and not mechanics of grading."

]]> Thu, 17 MAY 2012 17:52:27 AEST Geneva (AFP) April 24, 2012 - A professor at a Swiss university on Tuesday unveiled a robot that can be controlled by the brainwaves of a paraplegic person wearing an electrode-fitted cap, news agency ATS reported.

A paralysed man at a hospital in the town of Sion demonstrated the device, sending a mental command to a computer in his room, which transmitted it to another computer that moved a small robot 60 kilometres (37 miles) away in Lausanne.

The system was developed by Jose Millan, a professor at the Federal Polytechnic School of Lausanne who specialises in non-invasive interfaces between machines and the brain.

The same technology can be used to drive a wheelchair, Millan said.

"Once the movement has begun, the brain can relax, otherwise the person would soon be exhausted," he said.

But the technology has its limits, he added. The brain signals can be scrambled if too many people are gathered around a wheelchair, for example.

Besides making paraplegics mobile, neuroprosthetics could be used to help patients recover lost senses, researchers said.

Professor Stephanie Lacour and her team are working on an "electric skin" for amputees, a glove fitted with tiny sensors that would send information directly to the user's nervous system.

Eventually, researchers say they hope to create mechanised prosthetics that are as mobile and sensitive as a natural hand, Lacour said.

Other researchers at Lausanne are working on enabling paraplegics to walk again with electrodes implanted in their spinal cords.

"The goal is that after a year of training with a robotic aide, the patient will be able to walk without a robot. The electrodes would stay implanted for life," said Professor Gregoire Courtine.

He said he is currently setting up clinical trials and hopes to run tests at Zurich's university hospital within a year.

]]> Thu, 17 MAY 2012 17:52:27 AEST Chicago IL (SPX) Apr 25, 2012 - A new Northwestern Medicine brain-machine technology delivers messages from the brain directly to the muscles - bypassing the spinal cord - to enable voluntary and complex movement of a paralyzed hand. The device could eventually be tested on, and perhaps aid, paralyzed patients.

"We are eavesdropping on the natural electrical signals from the brain that tell the arm and hand how to move, and sending those signals directly to the muscles," said Lee E. Miller, the Edgar C. Stuntz Distinguished Professor in Neuroscience at Northwestern University Feinberg School of Medicine and the lead investigator of the study, which was published in Nature.

"This connection from brain to muscles might someday be used to help patients paralyzed due to spinal cord injury perform activities of daily living and achieve greater independence."

The research was done in monkeys, whose electrical brain and muscle signals were recorded by implanted electrodes when they grasped a ball, lifted it and released it into a small tube. Those recordings allowed the researchers to develop an algorithm or "decoder" that enabled them to process the brain signals and predict the patterns of muscle activity when the monkeys wanted to move the ball.

These experiments were performed by Christian Ethier, a post-doctoral fellow, and Emily Oby, a graduate student in neuroscience, both at the Feinberg School of Medicine. The researchers gave the monkeys a local anesthetic to block nerve activity at the elbow, causing temporary, painless paralysis of the hand.

With the help of the special devices in the brain and the arm - together called a neuroprosthesis - the monkeys' brain signals were used to control tiny electric currents delivered in less than 40 milliseconds to their muscles, causing them to contract, and allowing the monkeys to pick up the ball and complete the task nearly as well as they did before.

"The monkey won't use his hand perfectly, but there is a process of motor learning that we think is very similar to the process you go through when you learn to use a new computer mouse or a different tennis racquet. Things are different and you learn to adjust to them," said Miller, also a professor of physiology and of physical medicine and rehabilitation at Feinberg and a Sensory Motor Performance Program lab chief at the Rehabilitation Institute of Chicago.

Because the researchers computed the relationship between brain activity and muscle activity, the neuroprosthesis actually senses and interprets a variety of movements a monkey may want to make, theoretically enabling it to make a range of voluntary hand movements.

"This gives the monkey voluntary control of his hand that is not possible with the current clinical prostheses," Miller said.

The Freehand prosthesis is one of several prostheses available to patients paralyzed by spinal cord injuries that are intended to restore the ability to grasp. Provided these patients can still move their shoulders, an upward shrug stimulates the electrodes to make the hand close, a shrug down stimulates the muscles to make the hand open.

The patient also is able to select whether the prosthesis provides a power grasp in which all the fingers are curled around an object like a drinking glass, or a key grasp in which a thin object like a key is grasped between the thumb and curled index finger.

In the new system Miller and his team have designed, a tiny implant called a multi-electrode array detects the activity of about 100 neurons in the brain and serves as the interface between the brain and a computer that deciphers the signals that generate hand movements.

"We can extract a remarkable amount of information from only 100 neurons, even though there are literally a million neurons involved in making that movement," Miller said. "One reason is that these are output neurons that normally send signals to the muscles. Behind these neurons are many others that are making the calculations the brain needs in order to control movement. We are looking at the end result from all those calculations."

]]> Thu, 17 MAY 2012 17:52:27 AEST Pohang, South Korea (UPI) Apr 18, 2012 - South Korea has begun testing the feasibility of using robots as prison guards by deploying them in an actual prison in Pohang, officials said.

The robots' initial duty is to patrol the halls between cells looking for signs of trouble, and if detected alert human guards who will take appropriate action, PhysOrg.com reported Wednesday.

Dubbed Robo-Guard by the press, the robots carry several cameras, including a 3D one, microphone, speaker and circuitry, and are programmed with software that allows them to move autonomously in predefined areas inside the prison.

The software also allows the robots analyze inmates' behavioral characteristics to help in deciding whether assistance of human guards is needed.

The robots' main purpose, the Asian Forum of Corrections said, is to reduce manpower costs in prisons and create a safer environment for both inmates and those that guard them.

The current test trial, using three robots, is scheduled to last one month.

]]> Thu, 17 MAY 2012 17:52:27 AEST Subscribe to our daily selection of space, military, environment and energy newsletters responseText http://visitor.constantcontact.com/manage/optin/ea?v=0016gbbKsaiGSpQFojVO8ZoHw%3D%3D