Reasoning About Grasping From Task Descriptions

The advent of multiple degree of freedom, dextrous robot hands has made robot hand control more complicated. Besides the existing problem of finding a suitable grasping position and ap-proach orientation, it is now necessary to decide the appropriate hand shape to use for a given task. In order to deal with this additional complexity, we focus on how to represent prehensile tasks for mapping task descriptions into suitable hand shapes, positions and orientations. A generic robot hand control system GeSAM is being implemented to refine task descriptions into suitable dextrous robot hand shapes using Knowledge Craft on a TI lisp machine.