Vision-based three-finger grasp synthesis constrained by hand geometry

This paper addresses the problem of designing a practical system able to grasp real objects with a three-fingered robot hand. A general approach for synthesizing two- and three-finger grasps on planar unknown objects is presented. Visual perception is used to reduce the uncertainty and to obtain relevant information about the objects.We focus on non-modeled planar extruded objects, which can represent many real-world objects. In addition, particular mechanical constraints of the robot hand are considered.First, a vision processing module that extracts from object images the relevant information for the grasp synthesis is developed. This is completed with a set of algorithms for synthesizing two- and three-finger grasps taking into account force-closure and contact stability conditions, with a low computational effort. Finally, a procedure for constraining these results to the kinematics of the particular hand, is also developed. In addition, a set of heuristic metrics for assessing the quality of the computed grasps is described.All these components are integrated in a complete system. Experimental results using the Barrett hand are shown and discussed.