Augmented Neuromuscular Gait Controller Enables Real-time Tracking of Bipedal Running Speed

Abstract

Reproducing human locomotion in simulation has a variety of applications, from informing prosthetic and rehabilitation medicine to generating stable and human-like robot or animated character movement. In prior work, however, the focus has been on producing stable, natural gaits at a single speed. Novel neuromuscular controllers blending feedforward and reflex-like control have shown promising success in realizing bio-inspired speed-modulation of walking gaits while adapting a handful of parameters. In this work, we present a modified neuromuscular gait controller in the sagittal plane to similarly realize speed modulation for running gaits. As a result, our controller interpolates fewer than 10 parameters from a stable initialization to realize a large range of running speeds on a simulated bipedal platform. We discuss the speed-evolution and kinematic significance of these selected parameters, and analyze the controller's velocity-tracking performance over the speed range between 1.3 mls and 1.7 mis, which covers much of human running speeds once scaled from platform height.