Re-Using Schematic Grasping Policies
MASSACHUSETTS UNIV AMHERST DEPT OF COMPUTER SCIENCE
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It can be difficult to generalize the solutions to grasping and manipulation problems because even small differences in problem context can require qualitatively different solutions. For example, small changes in the shape of an object to be grasped can necessitate different grasp strategies. In this paper, the authors introduce the action schema framework that represents generalized skills in a functional way such that all viable ways of accomplishing a task are represented as instantiations of the generalized skill. They also propose an on-line algorithm for learning how to instantiate the skill in a context-appropriate way. They test this approach with a robotic grocery bagging task in which a dexterous humanoid robot learns to make correct qualitative decisions regarding how to grasp everyday grocery items and drop them in a paper bag.
- Human Factors Engineering and Man Machine Systems