Vision-based Path Following of Snake-like Robots
Lixing Liu, Wei Xi, Xian Guo, Yongchun Fang
Abstract
Due to the head swinging and the body winding, the self-localization and path following for snake-like robots based on vision are very challenging. In this paper, a novel pantilt compensation method and curve parameter compensation path following controller are proposed to solve these problems, which can achieve high-precision path following. More specifically, to realize real-time positioning of the snakelike robot, a camera-mounted pan-tilt is equipped on the head of the snake-like robot, and the Apritag detection is used after the angle between the Apriltag plane and the camera plane being compensated. Then, due to the modeling approximation, the snake-like robot with a simplified controller usually deviates from the desired path, so a curve parameter compensation path following controller is proposed to eliminate the deviation and improve the following accuracy. Finally, the experiments show that with proposed methods, the snake-like robot can converge to the desired path stably and accurately.
BibTeX
@inproceedings{icra2021_visionbasedpathf,
title = {Vision-based Path Following of Snake-like Robots},
author = {Lixing Liu and Wei Xi and Xian Guo and Yongchun Fang},
booktitle = {ICRA 2021},
year = {2021}
}