Rajesh Rao, associate professor of computer science and engineering, and his students have demonstrated that an individual can “order” a robot to move to specific locations and pick up specific objects merely by generating the proper brain waves that reflect the individual’s instructions.

The results were presented last week at the Current Trends in Brain-Computer Interfacing meeting in Whistler, B.C.

“This is really a proof-of-concept demonstration,” Rao says. “It suggests that one day we might be able to use semi-autonomous robots for such jobs as helping disabled people or performing routine tasks in a person’s home.”

The controlling individual – in this case a graduate student in Rao’s lab – wears a cap dotted with 32 electrodes. The electrodes pick up brain signals from the scalp based on a technique called electroencephalography. The person watches the robot’s movements on a computer screen via two cameras, one mounted on the robot and another above it.

Right now, the “thought commands” are limited to a few basic instructions. A person can instruct the robot to move forward, choose one of two available objects, pick it up, and bring it to one of two locations. Preliminary results show 94 percent accuracy in choosing the correct object.

Objects available to be picked up are seen by the robot’s camera and conveyed to the user’s computer screen. Each objects lights up randomly. When the person looks at the object that he or she wants to pick up and sees it suddenly brighten, the brain registers surprise. The computer detects this characteristic surprised pattern of brain activity and conveys the choice back to the robot, which then proceeds to pick up the selected object. A similar procedure is used to determine the user’s choice of a destination once the object has been picked up.

“One of the important things about this demonstration is that we’re using a ‘noisy’ brain signal to control the robot,” Rao says. “The technique for picking up brain signals is non-invasive, but that means we can only obtain brain signals indirectly from sensors on the surface of the head, and not where they are generated deep in the brain. As a result, the user can only generate high-level commands such as indicating which object to pick up or which location to go to, and the robot needs to be autonomous enough to be able to execute such commands.”

Rao’s team has plans to extend the research to use more complex objects and equip the robot with skills such as avoiding obstacles in a room. This will require more complicated commands from the “master’s” brain and more autonomy on the part of the robot.
“We want to get to the point of using actual objects that people might want the robot to gather, as well as having the robot move through multiple rooms,” Rao says.

One goal of future research is to make the robot’s behavior more adaptive to the environment, which means the robot’s programming must enable some kind of learning to occur. Rao’s team is well positioned for such research because it is one of the few groups in the world simultaneously investigating ways of controlling robots with brain waves and exploring advanced ways for robots to learn from experience.

Early in the experiments, Rao considered the question of whether the robot should be equipped with wheels rather than legs, which in some settings might make movement easier and more stable.

“We thought about this, but decided that our goal was to design applications for a human-centered environment in the home or work place,” he says. “So, to move and perform in those environments, the robot would have to be humanoid – to walk up stairs, for example, and to grasp objects designed for human use.”

For the demonstration, the robot was in a different room but in the same building as its human “master.” However, physical proximity is not a requirement for this brain-computer system to work: the individual and the robot can be anywhere in the world as long as there is Internet connectivity between their two locations.

Robots that act as human “agents” are a staple of science fiction literature and futuristic television shows like “The Jetsons,” in which the family had a robotic maid. Rao calls what his team has done “a primitive first step” down this road.

Video demonstration is available: http://uwnews.washington.edu/ni/video/movie_robot3.swf

Source: University of Washington

Why do human beings still risk their lives burrowing miles under ground and doing one of the dirtiest and most dangerous jobs in the world?

It’s an increasingly urgent question, given the recent high-profile mining accidents in Sago, W.Va., and Huntington, Utah. A small corps of engineers and robotics experts envision a day in the not-too-distant future when robots and other technology do most of the dangerous mining work, and even help rescue trapped miners.

Read the story at NPR 

“Superbot consists of Lego-like but autonomous robotic modules that can reconfigure into different systems for different tasks. Examples of configurable systems include rolling tracks or wheels (for efficient travel), spiders or centipedes (for climbing), snakes (for burrowing in ground), long arms (for inspection and repair in space), and devices that can fly in micro-gravity environment.

“Each module is a complete robotic system and has a power supply, micro- controllers, sensors, communication, three degrees of freedom, and six connecting faces (front, back, left, right, up and down) to dynamically connect to other modules.

“This design allows flexible bending, docking, and continuous rotation. A single module can move forward, back, left, right, flip-over, and rotate as a wheel. Modules can communication with each other for totally distributed control and can support arbitrary module reshuffling during their operation.  “They have both internal and external sensors for monitoring self status and environmental parameters. They can form arbitrary configurations (graphs) and can control these configurations for different functionality such as locomotion, manipulation, and self-repair.”

Shen illustrated his words with SuperBot action video showing these processes.

He and his colleagues and students made the fillms in just one week, immediately after completing the mechanics and electronics hardware for the latest batch of SuperBot modules at the beginning of February.

“The fact that SuperBot can achieve so much in so short a time demonstrates the unique value of modular, multifunctional and self-reconfigurable robots,” Shen said.

Source:  University of Southern California 

Previously AI researchers have tended not to try mimicking humour, largely because the human sense of humour is so subjective and complex, making it difficult to program.

Now Julia Taylor and Lawrence Mazlack of the University of Cincinnati in Ohio have built a computer program or “bot” that is able to get a specific type of joke – one whose crux is a simple pun. They say this budding cyber wit could lend a sense of humour to physical robots acting as human companions or helpers, which will need to be able to spot jokes if they are to be accepted and not just annoy people. 

Rest of the article at NewScientistTech 

 Techno blogger Al Fin tackles these questions in his interesting blog. 

 Read the article at National Geographic. 

A robot like Domo could help elderly or wheelchair-bound people with simple household tasks like putting away dishes. Other potential applications include agriculture, space travel and assisting workers on an assembly line, says Aaron Edsinger, an MIT postdoctoral associate who has been working on Domo for the last three years.

Edsinger describes Domo as the “next generation” of earlier robots built at MIT–Kismet, which was designed to interact with humans, and Cog, which could learn to manipulate unknown objects. Domo incorporates elements of both of those robots.

An assistive robot has to be able to sense when a human is touching it. Domo has springs in its arms, hands and neck that can sense force and respond to it. Photo / Donna Coveney

“The real potential of robots in the future is going to be realized when they can do many types of manual tasks,” including those that require interaction with humans, Edsinger said.

There are now plenty of robots doing manual work on factory assembly lines, but those machines follow a script and can’t learn to adapt to new situations, as Domo can, said Rodney Brooks, director of MIT’s Computer Science and Artificial Intelligence Laboratory.

“Robots in an automobile factory manipulate objects, but they do the same thing, along the same path, every time,” Brooks said. “If robots are ever going to be truly useful, they need to be able to manipulate the objects we manipulate.”

Living in the real world

Edsinger’s team, overseen by Brooks, decided to focus on making a robot that can function in a real human environment–in someone’s kitchen, for example. Robots that are designed to help people in their homes will have to be able to ignore the clutter found in most environments and focus only on certain stimuli, says Edsinger.

“Typically robots are placed in very restricted worlds because then you can control the environment. If you put a robot in someone’s home, that approach just doesn’t extend to that,” he said. “We want the robot to adapt to the world, not the world to adapt to the robot.”

Perched on a table in Edsinger’s workspace, Domo can “see” everything going on in front of it. As the robot’s large blue eyes roam across the room, cameras feed information to 12 computers that analyze the input and decide what to focus on.

Domo’s visual system is attuned to unexpected motion, allowing it to focus on important stimuli within human environments. For example, locating human faces is critical for social interaction, and people are often in motion. When Domo spots motion that looks like a face, it locks its gaze onto it.

Edsinger recently demonstrated how Domo can interact with people to help them accomplish useful tasks.

Once he captures Domo’s gaze, they exchange greetings. “Hey, Domo,” Edsinger says, to which Domo responds, “Hey, Domo.” “Shelf, Domo,” says Edsinger, prompting the robot to find a shelf. Domo looks around until it spots a nearby table that looks promising. The robot reaches out its left hand to touch the shelf, much like a person groping for a light switch in the dark, to make sure the shelf is really there.

Once Domo has located the shelf, it reaches out its right hand towards Edsinger, who places a bag of coffee beans in the open hand. Domo wiggles them a little to get a feel for the object, then transfers the bag from its right hand to its left hand (nearest the shelf). Domo then reaches up and places the bag on the shelf.

Though it seems like a minor movement, wiggling the object is key to the robot’s ability to accurately place it on a shelf, Edsinger says. Domo is programmed to learn about the size of an object by focusing on the tip of the object, for example, the cap of a water bottle. When the robot wiggles the tip back and forth, it can figure out how big the bottle is and decide how to transfer it from hand to hand or to place it on a shelf.

“You can hand it an object it’s never seen before, and it can find the tip and start to control it,” Edsinger said.

The human connection

The philosophy behind the team’s approach is that humans and robots can work together to accomplish tasks that neither could do all alone.

“If you can offload some parts of the process and let the robot handle the manual skills, that is a nice synergistic relationship,” Edsinger said. “The key is that it has to be more useful or valuable than the effort put into it.”

For Domo or any robot to safely interact with humans, the robot has to be able to sense when a human is touching it. Domo has springs in its arms, hands and neck that can sense force and respond to it. If you grab its hand and push, the robot will move the way you want it to.

“By placing that spring in there, you get physical compliance that makes the whole body sort of springy, which makes it safer for human interaction,” Edsinger said. But if you apply too much force or move Domo’s arms in the wrong direction, it voices its displeasure by saying “ouch.”

If robots are going to be useful in the home, it’s also important for them to have a humanoid form, so people will feel more comfortable around them.

Such assistive robots could be very useful in finding solutions to the impending health care crisis caused by the aging of the baby boomers, Edsinger said. Having help with simple tasks, such as getting a glass from a cabinet, could make a big difference for elderly or wheelchair-bound people.

The original work on Domo was funded by NASA, and the project is now supported by Toyota, which is interested in developing partner robots for the home. Another application is in assembly line production. The idea is that intelligent robots could work together with people to make workers more productive and save manufacturing jobs from being sent overseas, says Edsinger.

Although a life of leisure enabled by robots who perform all manual labor is still securely in the realm of science fiction, Brooks says he can foresee a future where robots specialized for different functions help out with household chores.

“I don’t think there’s going to be one Rosie the robot doing everything in the home,” said Brooks. “It’s more likely to be a team of robots doing different things.“Source: MIT , Anne Trafton, MIT News Office

Navigation is one of the biggest challenges faced by mobile robots. One popular technique, dubbed SLAM (simultaneous localisation and mapping), involves having a robot build a map of the local area, whilst also tracking its position.

Now, George Lee and colleagues at Purdue University, US, have come up with an altogether different approach. They have developed an algorithm that uses information already collected to “guess” what comes next.

Read the article at NewScientistTech.

Bucking the trend, a small coterie of devoted professionals and amateurs are working to make fully articulated, humanoid and even sinuously dancing robots a reality.

Read the article at Wired.