Adaptation of limit-cycle walkers for collaborative tasks: A supervisory switching control approach

Abstract

This paper presents a method to achieve online gait adaptation of a dynamically walking biped when collaborating with an external agent-either a human or a robot-acting as a leader. Adaptation occurs without any explicit information on the leader's intended motion; only implicit information is used through the interaction force developed between the leader and the biped. An adaptive supervisory control scheme is proposed and guarantees for boundedness of the state despite switching under external force are provided. The supervisory controller leverages the availability of a library of exponentially stable limit-cycle gaits, and orchestrates switching among them in an online fashion to achieve adaptation. As a result, the range of leader speeds that the biped can adapt to is drastically enlarged while the leader's effort is reduced.