Whole-Body Path Following of an Active-Joint Active-Wheel Snake Robot Based on Head-Body Stepwise Control
Fuxi Wan, Xian Guo, Huawang Liu, Wei Huang, Zhong Huang
Abstract
This paper presents a two-dimensional planar path-following controller for active-joint active-wheel snake-like robots. Compared to passive-wheel snake robots, active-wheel snake robots can navigate narrower spaces and generate stronger driving forces, enabling adaptation to various terrains. However, due to the highly redundant multi-link and multi-active-wheel body configuration, achieving whole-body path following for active-joint active-wheel snake robots is challenging. To address this, we propose a head-body stepwise path-following control method based on a multi-rigid-body kinematic model to solve the problem of high degrees of freedom and the coordination between joints and wheels. First, by applying the no-side-slip constraint, we construct a multi-joint and multi-wheel kinematic model for the snake body path-following control task. Then, a motion controller is designed for the fundamental motion of the active wheeled snake robot. To achieve path following, an arbitrary path following controller is designed for turning angle. Then, the designed turning angle is substituted into the motion controller, and the angular velocity of each joint is calculated based on kinematic model. Subsequently, an incremental PID controller is designed to control the angle of each joint. Finally, the whole-body path following task of active-wheel snake-like robot can be implemented. Simulation and extensive experimental results for both curvature-continuous and curvature-discontinuous paths demonstrate the superior following performance of the proposed controller compared to the PD method and passive-joint conditions. Furthermore, the robustness of the proposed method to variations in friction is validated.
BibTeX
@inproceedings{ral2026_wholebodypathfol,
title = {Whole-Body Path Following of an Active-Joint Active-Wheel Snake Robot Based on Head-Body Stepwise Control},
author = {Fuxi Wan and Xian Guo and Huawang Liu and Wei Huang and Zhong Huang},
booktitle = {RA-L 2026},
year = {2026}
}