Control of Planar Spring–Mass Running Through Virtual Tuning of Radial Leg Damping

Abstract

Existing research on dynamically capable legged robots, particularly those based on spring–mass models, generally considers improving in isolation either the stability and control accuracy on the rough terrain, or the energetic efficiency in steady state. In this paper, we propose a new method to address both, based on the hierarchical embedding of a simple spring-loaded inverted pendulum (SLIP) template model with a tunable radial damping coefficient into a realistic leg structure with series-elastic actuation. Our approach allows using the entire stance phase to inject/remove energy both for transient steps and in steady state, decreasing the maximum necessary actuator power while eliminating wasteful sources of the negative work. In doing so, we preserve the validity of the existing analytic approximations to the underlying SLIP model, propose improvements to increase the predictive accuracy, and construct accurate, model-based controllers that use the tunable damping coefficient of the template model. We provide extensive comparative simulations to establish the energy and power efficiency advantages of our approach, together with the accuracy of model-based gait control methods.