Inverse Kinematics Computation based on Reachability Analysis

In this work we show how precomputed reachability information can be used to e ciently solve complex inverse kinematics (IK) problems such as bimanual grasping or re-grasping for humanoid robots. We present an integrated approach which generates collision-free IK solutions in cluttered environments while handling multiple potential grasping con gurations for an object. Therefore, the spatial reachability of the robot's workspace is e ciently encoded by discretized data structures and sampling-based techniques are used to handle arbitrary kinematic chains. The algorithms are employed for single-handed and bimanual grasping tasks with xed robot base position and methods are developed that allow to e ciently incorporate the search for suitable robot locations. The approach is evaluated in di erent scenarios with the humanoid robot ARMAR-III.