CPG Design using Inhibitory Networks

Abstract

We describe in detail the behavior of an inhibitory Central Pattern Generator (CPG) network for robot control. A four-neuron, mutual inhibitory network forms the basic coordinating pattern for locomotion. This network then inhibits an eight-neuron network used to drive patterned movement. We show that we can get predictable control of important relationships such as the phase of the hip and the knee by adjusting tonic parameters. We demonstrate the basic concept both in a simulation that is used to drive a trotting bipedal robot as well as an aVLSI CPG chip that generates spiking burst patterns. Our results indicate that an inhibitory framework can generate simple, understandable and flexible networks for legged robot control that can be implemented in custom VLSI circuits.