Balancing and Reaching with Model Predictive Control

HRP-2 balances while trying to reach a moving target (i.e. a simulated yellow ball moved by the user through a 3D mouse). The motion is generated online through MuJoCo, a fast trajectory optimization software based on the optimal-control algorithm iLQR and a smooth approximation of the contact dynamics. The control objectives are specified with a cost function, which was designed to make the robot i) balance, ii) reach the ball, iii) not take a step and iv) minimize joint torques and velocities.

Reference Paper

Whole-body Model-Predictive Control applied to the HRP-2 Humanoid. Jonas Koenemann, Andrea Del Prete, Yuval Tassa, Emanuel Todorov, Olivier Stasse, Maren Bennewitz and Nicolas Mansard. In Intelligent Robots and Systems (IROS 2015), IEEE International Conference on, 2015. (PDF) (BIBTEX)