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

This paper presents a practical approach for synthesizing two and three-finger grasps on planar unknown objects by means of vision. We make use visual perception to reduce the uncertainty and to obtain relevant information about the objects. Moreover, we focus on non-modeled planar extruded objects, that can represent most real-world objects. Finally, we also take into account the particular mechanical constraints of the hand, with particular application to the three-fingered Barrett Hand. Our approach contains three main components. First, a vision processing module that extracts from object images the relevant information for the grasp synthesis: a contour description and a set of feasible grasp regions. A second component is a set of algorithms for synthesizing two and three-finger grasps having into account force-closure and contact stability conditions, with a low computational effort. Finally, the third and most important component consists of a procedure for constraining these results to the kinematics of the particular hand, something that has not been considered by most authors. In addition, a set oh heuristic metrics for assessing the quality of the computed grasps is described. As a conclusion, we developed a complete grasping system that implements the components described, that is able to execute any of the grasps computed. Experimental results using the Barrett Hand are shown and discussed.