Image-based object recognition and dexterous hand/arm motion planning using RRTs for grasping in cluttered scene

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) multigoal and multicriteria path planning for 7 DOF 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.