• CN: 11-2187/TH
  • ISSN: 0577-6686

Journal of Mechanical Engineering ›› 2024, Vol. 60 ›› Issue (21): 4-13.doi: 10.3901/JME.2024.21.004

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Design and Experimental Study of Whole-body Obstacle Avoidance Strategy for Snake Robots

LI Peng1, WANG Liuyin2, WANG Gang2, MA Shugen3   

  1. 1. School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen 518055;
    2. The Institute of Machine Intelligence, University of Shanghai for Science and Technology, Shanghai 200093;
    3. Thrust of Robotics and Autonomous Systems, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou 511453
  • Received:2024-02-28 Revised:2024-06-13 Published:2024-12-24

Abstract: To solve the problems of low obstacle avoidance efficiency and collision of some joints with obstacles in micro snake robots, a new whole-body obstacle avoidance strategy for snake robots is proposed based on model predictive control. A guidance strategy is also proposed that is applicable to the unique structure of snake robots. The proposed obstacle avoidance strategy can both accurately follow the target path when there is no obstacle and efficiently avoid obstacles when there is an obstacle and quickly return to the original path. Different from the existing strategies that can only guarantee that the head or center of mass of the snake robot does not collide with obstacles, our proposed strategy can guarantee that all joints do not collide with obstacles, and the efficiency of obstacle avoidance is improved without considering the maximum collision volume or assuming that the snake’s tail moves strictly according to the trajectory of the snake’s head. In addition, by analyzing the effect of the changing drive structure of the snake robot on the turning efficiency under the fixed gait, a guidance strategy applicable to this type of robot with changing turning efficiency is proposed to avoid the oscillation phenomenon of the robot repeatedly shuttling through the desired path. The effectiveness of the proposed strategies is verified by extensive simulations and experiments.

Key words: snake robot, whole-body obstacle avoidance, model predictive control

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