Self-collision avoidance and angular momentum compensation for a biped humanoid robot

Abstract

To simplify the development of new trajectories for a humanoid robot with many joints, the ability to check for potential collisions is crucial. More importantly, to enable on line generation of general motions, such as whole-body-motion, collision avoidance must be employed, which is usually more challenging. In this paper, a model-based and efficient on-line distance calculation between links of the robot is proposed. To avoid collisions the results are projected into the null space term of the inverse-kinematics which is based on the redundancy resolution framework of LIEGEOIS. Additionally, a novel method to reduce the vertical angular momentum for a walking biped robot which uses the arm motion is proposed. It reduces the vertical angular momentum of the walking robot especially for larger steps. Since the method also works in the null-space, it can easily be combined with the proposed collision avoidance scheme. Finally, results for the proposed methods from simulations and experiments with the robot Lola are shown.