Collision Avoidance Algorithm for Unmanned Surface Vehicle Based on Improved Artificial Potential Field and Ant Colony Optimization

DOI

10.2991/cnci-19.2019.49How to use a DOI?

Keywords

Unmanned surface vehicle, collision avoidance, route planning, artificial potential field algorithm, ant colony algorithm.

Abstract

There is a growing concern to design collision avoidance algorithm for unmanned surface vehicle (USV) as a solution to many naval and civilian requirements. Due to the anti-jamming performance of the traditional collision avoidance algorithm decrease with the influence of environmental disturbances, resulting in the problems of frequent steering and overshoot when USV is sailing under harsh sea condition. An improved collision avoidance algorithm based on improved artificial potential field and ant colony optimization is proposed in this paper. And, a power function based on the change of the distance to the obstacle is proposed. This improved combination is to solve the problem of frequent steering and overshoot of USV's control system with good robustness during collision avoidance. The results of simulation and experiment demonstrate the proposed method is more efficient and more capable to avoid the obstacles through route planning particularly in the presence of large disturbances.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Wen Ou
AU  - Xuan Guo
PY  - 2019/05
DA  - 2019/05
TI  - Collision Avoidance Algorithm for Unmanned Surface Vehicle Based on Improved Artificial Potential Field and Ant Colony Optimization
BT  - Proceedings of the 2019 International Conference on Computer, Network, Communication and Information Systems (CNCI 2019)
PB  - Atlantis Press
SP  - 334
EP  - 347
SN  - 2352-538X
UR  - https://doi.org/10.2991/cnci-19.2019.49
DO  - 10.2991/cnci-19.2019.49
ID  - Ou2019/05
ER  -