Implementation of vision-based planar grasp planning

Abstract

This research describes the implementation of a vision-based algorithm that is capable of rapidly determining robotic grasp points for planar objects. A representation of the target and a quadtree expansion generate candidate grasps that are compared using a cost function. The approach returns the first acceptable grasp point at a given tree resolution. The system has an execution time on the order of seconds and it is suitable for a large number of planar or near planar objects.