Swing Leg Motion Strategy for Heavy-load Legged Robot Based on Force Sensing

TL;DR

This paper presents a force sensing-based swing leg motion strategy for heavy-load legged robots, improving stability, terrain adaptability, and energy efficiency through a finite state machine model inspired by elephant movement.

Contribution

Introduces a novel swing leg control method using force sensing and terrain information to enhance robustness and success rate in complex terrains for heavy-load robots.

Findings

Method improves stepping success rate

Enhances robustness on complex terrains

Enables smooth autonomous navigation

Abstract

The heavy-load legged robot has strong load carrying capacity and can adapt to various unstructured terrains. But the large weight results in higher requirements for motion stability and environmental perception ability. In order to utilize force sensing information to improve its motion performance, in this paper, we propose a finite state machine model for the swing leg in the static gait by imitating the movement of the elephant. Based on the presence or absence of additional terrain information, different trajectory planning strategies are provided for the swing leg to enhance the success rate of stepping and save energy. The experimental results on a novel quadruped robot show that our method has strong robustness and can enable heavy-load legged robots to pass through various complex terrains autonomously and smoothly.