Discovering Optimal Natural Gaits of Dissipative Systems via Virtual Energy Injection

TL;DR

This paper introduces a unified framework for discovering energy-efficient natural gaits in dissipative legged robots by leveraging their passive dynamics through a novel energy injection method and continuation approach.

Contribution

It presents a new energy injection technique and a continuation method to identify passive motions and derive energy-optimal control inputs for dissipative robotic systems.

Findings

Successfully identified passive motion patterns in simulated models.

Derived energy-optimal control inputs for fully actuated, dissipative systems.

Demonstrated applicability in single- and multi-legged robots.

Abstract

Legged robots offer several advantages when navigating unstructured environments, but they often fall short of the efficiency achieved by wheeled robots. One promising strategy to improve their energy economy is to leverage their natural (unactuated) dynamics using elastic elements. This work explores that concept by designing energy-optimal control inputs through a unified, multi-stage framework. It starts with a novel energy injection technique to identify passive motion patterns by harnessing the system's natural dynamics. This enables the discovery of passive solutions even in systems with energy dissipation caused by factors such as friction or plastic collisions. Building on these passive solutions, we then employ a continuation approach to derive energy-optimal control inputs for the fully actuated, dissipative robotic system. The method is tested on simulated models to demonstrate its applicability in both single- and multi-legged robotic systems. This analysis provides valuable insights into the design and operation of elastic legged robots, offering pathways to improve their efficiency and adaptability by exploiting the natural system dynamics.