Underactuated Virtual Gravity Control: Harnessing Passive Dynamics for Optimally Efficient Bipedal Locomotion

Abstract

This paper explores the Underactuated Virtual Gravity (UVG) controller, a model-based control approach designed to achieve energy-efficient bipedal walking. The UVG controller minimizes actuator effort during level-ground walking by capitalizing on the inherent dynamics that facilitate stable passive gaits on downward slopes. By effectively leveraging torso dynamics to support the application of the UVG, the method turns the innate underactuation of bipedal systems into an advantage. Extensive benchmarking against state-of-the-art methods such as the Trajectory Optimization for trajectory planning combined with Non-linear Model Predictive Control for tracking shows that the UVG achieves superior energy efficiency within its effective range while constituting a closed-form controller that requires fewer computational resources than numerical methods. The results highlight the UVG and related dynamics-based approaches as a compelling option for energy-conscious, task-focused robot designs.