Detecting surface features during locomotion using optic flow

Abstract

We test the hypothesis that: (1) Optic flow can be used to detect significant environmental features during locomotion in a biped, even given significant up and down movement and jarring of the robot during locomotion. (2) Reliable detection is only possible if a prediction of the expected optic flow field is made at each instance. This prediction should be driven by the phase of the robot's gait as well as other information about the state of the robot. (3) This prediction can be accomplished in a distributed, biologically plausible framework. Our results using a walking biped mechanism strongly support this hypothesis and indicate that optic flow is a viable strategy and that the prediction of optic flow is a critical component in this behavior.