Robot hand learns real world moves in VR

Researchers backed by Tesla Inc founder Elon Musk and Silicon Valley financier Sam Altman have found a novel way to use software to teach a human- like robotic hand new tasks, a discovery that could eventually make it more economical to train robots to do things that are easy for humans.

Researchers at OpenAI, a nonprofit artificial intelligence research group founded in 2015, said on Monday they had taught a robotic hand to rotate a lettered, multi- coloured block until a desired side of the block faces upward.

The task is simple. But the advance was in how the hand gained the skill: All the learning happened in a software simulation and was then transferred to the physical world with relative ease.

That solves a challenge for robotic hands, which look like the fist of a robot from the 1980s ‘ Terminator’ science fiction film. The hands have been commercially available for years but are difficult for engineers to program. Engineers can write specific computer code for each new task, which requires a pricey new program each time. Or robots can be equipped with software that lets them “learn” through physical training.

Physical training takes months or years and has problems of its own — for example, if a robot hand drops a workpiece, human needs to pick it up and put it back. That is expensive as well. Researchers have sought to chop up those years of physical training and distribute them to multiple computers for a software simulation that can do the training in hours or days, without human help. Ken Goldberg, a University of California Berkeley robotics professor who was not involved in the OpenAI research but reviewed it, called the OpenAI work “an important result” in getting closer to that goal.

“That’s the beauty of having lots of computers crunching on this, Goldberg said. “You don’t need any robots and just have lots of simulation,” — Reuters