Stride-level control of quadrupedal runners through optimal scaling of hip-force profiles

Abstract

This thesis presents Optimally Scaled Hip-Force Planning (OSHP), a novel approach to controlling the body dynamics of running robots. Controllers based on this approach form the high-level component of a hierarchical control scheme in which they direct lower level controllers, each responsible for coordinating the motion of a single leg. An OSHP controller takes in the state of the runner at the apex of its primary aerial phase and returns desired profiles for the vertical and horizontal forces to be exerted at each hip during the subsequent stride. Controlling the legs so as to match these profiles is left to the lower level leg controllers. The hip force profiles returned by OSHP are scaled variants of nominal force profiles based on biological ground reaction force data. The OSHP controller determines the scaling parameters for these profiles through constrained nonlinear optimization on an approximate model of the runner's body dynamics. Additionally this thesis presents an implementation of an OSHP controller for a simple quadruped model. Evaluation of the controller in simulation shows that even with very simple leg controllers, the OSHP controller can produce bounding and pronking gaits in that model. These gaits emerge as the controller attempts to match particular targets for the runners' states at the apex of their strides. The order in which the feet make contact with ground is not pre-specified. That evaluation also shows that the OSHP controller can compensate for errors introduced by the leg controllers to match given target values for the runners' height, pitch, and pitch rate at the apex of their strides.