Experiments with a hierarchical inverse dynamics controller on a torque-controlled humanoid

Recently several hierarchical inverse dynamics controllers based on quadratic programs have been proposed for application to torque controlled robots. They have important theoretical benefits but have never been implemented on a torque controlled robot where model inaccuracies and realtime computation requirements can be problematic. In this contribution we present experimental results for the control of the lower body of a humanoid robot using these algorithms. We propose a simplification of the optimization problem that allows us to decrease computation time enough to implement it in a fast torque control loop. Experiments demonstrate the applicability of the approach. In a first experiment, we implement a momentum-based balance controller which shows robust performance in face of unknown disturbances. In a second experiment, a tracking task is evaluated to demonstrate the performance of the controller with more complicated hierarchies. Our results show that hierarchical inverse dynamics controllers can be efficiently used for feedback control of humanoid robots and that momentum-based balance control can be efficiently implemented on a real robot.