Detecting surface features during locomotion using optic flow

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.