Learning to walk efficiently with passive compliance
The compliant humanoid robot COMAN learns to walk with two different gaits: one with fixed height of the center of mass, and one with varying height. The varying-height center-of-mass trajectory was learned by reinforcement learning in order to minimize the electric energy consumption during walking. The optimized walking gait achieves 18% reduction of the energy consumption in the sagittal plane, due to the passive compliance - the springs in the knees and ankles of the robot are able to store and release energy efficiently. In addition, the varying-height walking looks more natural and smooth than the conventional fixed-height walking.