(Article by Matthew Hutson from ScienceMag.org)
A 5-year-old can tie their shoelaces, but robot hands aren’t nearly so nimble. A new system, however, has greatly improved their dexterity.
Hard-coding a robot to coordinate multiple joints is daunting. So computer scientists have turned to machine learning, a field of artificial intelligence (AI) in which computers build skills on their own. Such learning takes time and repetition, however, and robot hardware is slow and breakable. Some researchers instead train algorithms with virtual robots, but reality is always slightly different from simulation.
The new work overcame this “reality gap” by slightly randomizing elements of the simulation during training, such as friction and object size. (Most of the work, in both simulation and reality, was done with a child’s building block with letters on its sides.) They also gave the program short-term memory, so after a few seconds of handling the cube, it got a sense of the block’s exact size and other factors and adjusted for them.