Elegant Stepping: A Model of Visually Triggered Gait Adaptation

Abstract

Existing visually guided walking machines have difficulty traversing terrain cluttered with obstacles. These walking machines use computationally intense approaches that require construction of a geometrically correct model of both the environment and the robot. However, most terrestrial vertebrates accomplish this task easily suggesting that better strategies exist. We present a model inspired by recent research in cats and humans. In our model, perception and action are tightly coupled. The mapping is adaptive and based on experience. The goal of the adaptation is to use distance measurements to smoothly modulate a Central Pattern Generator (CPG) controlling gait. A key element in our model is the use of a temporal gating hypothesis. This hypothesis simplifies the learning problem and is consistent with biological observations. Our approach does not require that a geometric representation of the environment be created or updated based on new observations. This is in strong contrast t...