Generating and evaluating regrasp operations

Abstract

Regrasping must be performed whenever a robot's grasp of an object is not compatible with the pick-and-place operation the robot must perform. This paper presents a new approach to the problem of regrasping for a robot arm equipped with a parallel-jaw end-effector. The method employs an evaluated breadth-first search in the space of compatible regrasp operations taking into account several criteria rating about the grasp and placement quality. We pay particular attention to online computational efficiency. The presented system is the first planning system performing as much of offline computation as possible for solving the regrasp problem efficiently online.