Towards understanding visually guided locomotion over complex and rough terrain: A phase-space planning method

Abstract

As legged robots maneuver over increasingly complex and rough terrains, designing motion planners with the capability of predicting future footsteps becomes imperative. In turn, these planners provide a valuable tool for understanding the fundamental principles underlying human locomotion [2, 3]. In this study, we use our previously proposed phase-space planning framework [1] to analyze human walking over complex terrain. In particular, we highlight (i) the center of mass (CoM) apex-state-based feature of the phase-space planning, and (ii) the role of vision in CoM apex state selection during human walking over complex terrain [2].