Abstract
Fast Damage Recovery through Learning
While animals can quickly adapt to a wide variety of injuries, current robots cannot “think outside the box” to find a compensatory behavior when dam- aged: they are either limited to the contingency plans provided by their design- ers, or need many hours to search for suitable compensatory behaviors. We introduce an intelligent trial and error algorithm that allows robots to adapt to damage in less than 2 minutes, thanks to intuitions that they develop before their mission and experiments that they conduct to validate or invalidate them after damage. The result is a creative process that adapts to a variety of in- juries, including damaged, broken, and missing legs. This new technique will enable more robust, effective, autonomous robots and suggests principles that animals may use to adapt to injury.