Autonomous Speed Adaptation by a Simulated Cat's Hind Legs and Evaluation of the Controller

Abstract

A major goal of this study is to design the nervous system model for quadrupedal locomotion. We apply a two-level central pattern generator (CPG) to our nervous system model, which generates locomotion rhythm and reproduces leg trajectories. And this nervous system model has an afferent sensory feedback, which uses leg loading, to CPGs. A cat hind leg model, which has six muscle models to drive three joints on each leg, is controlled using our nervous system model. When the locomotion speed of this model was forcibly increased by an external force, this model autonomously adapted to its speed and kept walking despite not changing any nervous system parameters. Since similar phenomena have been reported in animal experiments, our results suggest that our nervous system is an appropriate model.