Extensions to Reactive Self-Collision Avoidance for Torque and Position Controlled Humanoids

Abstract

One of the fundamental demands on robotic systems is a safe interaction with their environment. For fulfilling that condition, both collisions with obstacles and the own structure have to be avoided. We address the problem of self-collisions and propose an algorithm for its avoidance which is based on artificial repulsion potential fields and applicable to both torque and position controlled manipulators. To this end, we design a damping that incorporates the configuration dependance of the robot. For a maximum level of safety, an additional emergency brake strategy based on kinetic energy considerations is introduced for situations in which self-collisions are not avoidable by the controller. Experiments are performed on DLR's humanoid Justin.