A principled approach to biological motor control for generating humanoid robot reaching movements

This paper presents an application of neurobiological motor principles to the control of humanoid robot reaching movements. The model is mainly based on the hypotheses that the energy of motoneurons signals is continuously minimized along the motion and that dynamic and static efforts are processed separately. This paradigm is used to control the robot HRP2 by considering a dynamic model of the arm including, for each degree of freedom, two second order low-pass filters modeling the neuromuscular system defined by a pair of antagonist muscles. The optimal control problem is solved as a nonlinear programming problem by using a direct transcription method coupled with the optimization software Ipopt. This approach allows to generate realistic movements with anthropomorphic features such as quasi-rectilinear trajectories and bell-shaped velocity.