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, page 8p., 2015. (PDF) (BIBTEX)