EFFICIENT INVERSE KINEMATICS COMPUTATION BASED ON REACHABILITY ANALYSIS

Abstract

In this work we show how precomputed reachability information can be used to efficiently 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 configurations for an object. Therefore, the spatial reachability of the robot's workspace is efficiently 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 fixed robot base position and methods are developed that allow to efficiently incorporate the search for suitable robot locations. The approach is evaluated in different scenarios with the humanoid robot ARMAR-III.