The dynamic optimization approach to locomotion dynamics: human-like gaits from a minimally-constrained biped model

Abstract

This work presents a unifying framework to study energy-efficient optimal gaits for a bipedal model without elastic elements. The model includes a torso, flat feet, and telescoping legs, equipped with rotational hip and ankle joints. Two general types of gaits are studied: with and without a flight phase. The support surface can be level ground, sloped, or staircase. The algorithm achieves the optimum within the admissible space by using a minimal set of realistic physical constraints, and avoiding a priori assumptions on kinetic and kinematic parameters such as extended or instantaneous double-support, collisional or collisionless foot-ground contact, step length, step period, etc. The gait optimization for this simple model predicts many features of human locomotion including the optimality of pendular walking and impulsive running at slow and fast progression speeds, ankle push-off prior to touch-down, swing leg retraction, landing on a near vertical leg in gaits with flight phase, and burst hip torques at both ends of the swing phase.