Image-based Object Recognition and Dexterous Hand/Arm Motion Planning Using RRTs for Grasping in Cluttered Scene

摘要

This paper describes a new approach to realize grasping of an unknown object by a dexterous hand robot among freely placed multiple unknown objects even if they are occluded each other. This technology consists of major three functions: 1) image-based 3D reconstruction and separation of multiple objects using graph-cut theory, 2) recognition of the shape, size and orientation of each object as an object with primitive shape, i.e. either of box, cylinder or sphere, 3) multi-goal and multi-criteria path planning for 7 DOP arm with 13 DOF dexterous hand using enhanced RRTs (Rapidly-Exploring Random Trees) algorithm to cope with multiple possible grasping strategy according to the object shape and orientation.