A fast and robust grasp planner for arbitrary 3D objects

In order to grasp and manipulate real world objects, grasp planning systems are required, and they have to be very fast in order to be integrated in online planning systems for robots. This paper presents a method to compute a desirable grasp quality measure very fast and accurately. Based on this measure a heuristic approach towards fast planning of precision grasps for arbitrarily shaped 3D objects is described. A number of feasible grasp candidates are generated heuristically. These grasp candidates are qualified using the described grasp quality measure and the best candidate is chosen. The planned grasps are robust with respect to grasp placement. It is shown that only a relatively small number of grasp candidates has to be generated in order to obtain a good, although not optimal, grasp.