Chess robots have trouble grasping the game

Chess robots have trouble grasping the game
16:00 20 December 2011
Duncan Graham-Rowe, contributor

Deep Blue’s victory over Gary Kasparov in 1997 may have shown how computers can outsmart people, but if the game is taken into the physical world, humans still win hands down.

That’s because, for all their software smarts, robots remain clumsy at manipulating real-world objects. A robotic chess competition held in August, for example, showed that even robotic arms used for precise work on industrial manufacturing lines have trouble when asked to negotiate a noisy, chaotic real-world environment.

The contest, held at the Association for the Advancement of Artificial Intelligence annual conference in San Francisco, California, had a number of automatons competing to see who could best move pieces quickly, accurately and legally in accordance with the rules of chess.

Some teams used vision systems to identify where pieces were, but none attempted to distinguish between a rook and a knight, for example. Instead they relied upon remembering where pieces were last placed to identify them and move them accordingly.

The bots quickly ran into snags – their vision systems often misread moves, which led to confusion as to what piece had moved, and where the other pieces were on the board.

One approach, by robotics company Road Narrows, used a commercially available fixed robotic arm normally used for light industrial applications without any vision at all. The winner was a team led by Mike Ferguson at the University of Albany, in New York, which had a mobile robot with an arm attached. Despite the many variables introduced when moving a robot around, the droid’s vision system managed to keep track of the board and pieces as it moved about, says Mike Stilman, one of the event’s organisers, of Georgia Institute of Technology, in Atlanta.

But even Ferguson’s bot is a long way from earning the title “grand master” – all the teams’ chess tactics came from a standard open source program that wouldn’t have given Deep Blue a run for its money. But the creation of a software champion chess program wasn’t just about winning, Stilman says – it was about gaining an insight into how the human mind works in order to build smarter machines. By bringing the challenge into the real world, the hope is to do the same for the physical problems of robotics, he says.

Source: http://www.newscientist.com