Control Scheme and Uncertainty Considerations for Dynamic Balancing of Passive-Ankled Bipeds and Full Humanoids

Abstract

We propose a methodology for dynamically balancing passive-ankled bipeds and full humanoids. As dynamic locomotion without ankle-actuation is more difficult than with actuated feet, our control scheme adopts an efficient whole-body controller that combines inverse kinematics, contact-consistent feed-forward torques, and low-level motor position controllers. To understand real-world sensing and controller requirements, we perform an uncertainty analysis on the linear-inverted-pendulum (LIP)-based footstep planner. This enables us to identify necessary hardware and control refinements to demonstrate that our controller can achieve long-term unsupported dynamic balancing on our series-elastic biped, Mercury. Through simulations, we also demonstrate that our control scheme for dynamic balancing with passive-ankles is applicable to full humanoid robots.