Motion planning and bimanual coordination in humanoid robots

Abstract

Humanoid robots have a large number of “extra” joints, organized in a humanlike fashion with several kinematic chains. In this chapter we describe a method of motion planning that is based on an artificial potential field approach (Passive Motion Paradigm) combined with terminal-attractor dynamics. No matrix inversion is necessary and the computational mechanism does not crash near kinematic singularities or when the robot is asked to achieve a final pose that is outside its intrinsic workspace: what happens, in this case, is the gentle degradation of performance that characterizes humans in the same situations. Moreover, the remaining error at equilibrium is a valuable information for triggering a reasoning process and the search of an alternative plan. The terminal attractor dynamics implicitly endows the generated trajectory with human-like smoothness and this computational framework is characterized by a feature that is crucial for complex motion patterns in humanoid robots, such as bimanual coordination or interference avoidance: precise control of the reaching time.