Optimizing Dynamic Legged Locomotion in Mixed, Resistive Media

Abstract

Locomotion through resistive media is an organic occurrence during traversal of the natural world. Due to the complexities required to analyze the effect of these media on the dynamics of locomotion, controllers of legged robots generally neglect or treat them as disturbances. In this paper, we address the challenge of producing optimal locomotion control in resistive media. We do so by applying trajectory optimization techniques within a direct collocation framework onto a reduced-order resistive model of legged locomotion: the Fluid Field SLIP model. The results of this optimization led to five different optimal gaits being found for hopping in air, fluidized media, and at the interface between these fluids. When applying the optimal control policies to a single leg robotic hopper in mixed fluid it was found that the new controller was able to improve its efficiency by 54% over the previous controller. It achieved this by employing a novel "kickback" and retraction maneuver found by the optimizer. This maneuver was found to improve efficiency even in un-optimized controllers when hopping in deep fluid.