Simultaneous Grasp and Motion Planning

In this work, we present an integrated approach for planning collision-free grasping motions. The proposed Grasp–RRT planner combines the three main tasks needed for grasping an object: building a feasible grasp, solving the inverse kinematics problem and searching a collision-free trajectory that brings the hand to the grasping pose. Therefore, RRT-based algorithms are used to build a tree of reachable and collisionfree configurations. During RRT-generation, grasp hypotheses are generated and approach movements toward them are computed. The quality of reachable grasping poses is evaluated via grasp wrench space analysis. We also present an extension to a dual arm planner which generates bimanual grasps together with corresponding dual arm grasping motions. The algorithms are evaluated with different setups in simulation and on the humanoid robot ARMAR-III.