Running gait optimization for electrically actuated quadruped robots to exert their sport capability adapting to variable actuation limit

Abstract

This paper investigates how to further enhance the dynamic running performance of electrically actuated quadruped robots (e-QRs) under structural, actuation, and load constraints. While existing model predictive control frameworks typically rely on pre-defined gait sequences, we propose a gait sequence optimization method that adapts to variable motor limits and payload conditions to better exploit the robot’s motion capabilities. Experiments on a 518 kg battery-powered e-QR demonstrate a 27% improvement in outdoor running speed—from 1.8 m/s to 2.3 m/s—compared with a baseline using a fixed gait under the same controller.

Graphical abstract

Keywords

legged robots / optimization and optimal control / whole-body motion planning and control

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