Cooperative path planning of multiple autonomous underwater vehicles operating in dynamic ocean environment

Yufei Zhuang; Haibin Huang; Sanjay Sharma; Dianguo Xu; Qiang Zhang

doi:10.1016/j.isatra.2019.04.012

Cooperative path planning of multiple autonomous underwater vehicles operating in dynamic ocean environment

ISA Trans. 2019 Nov:94:174-186. doi: 10.1016/j.isatra.2019.04.012. Epub 2019 Apr 26.

Authors

Yufei Zhuang¹, Haibin Huang², Sanjay Sharma³, Dianguo Xu⁴, Qiang Zhang⁵

Affiliations

¹ School of Information Science and Engineering, Harbin Institute of Technology, Weihai, 264200, PR China.
² School of Information Science and Engineering, Harbin Institute of Technology, Weihai, 264200, PR China. Electronic address: huanghaibin@hitwh.edu.cn.
³ School of Engineering, Plymouth University, Plymouth, PL4 8AA, United Kingdom.
⁴ School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin, 150001, PR China.
⁵ Navigation College, Shandong Jiaotong University, Weihai, 264209, PR China.

PMID: 31047643
DOI: 10.1016/j.isatra.2019.04.012

Abstract

This paper presents a two-stage cooperative path planner for multiple autonomous underwater vehicles operating in dynamic environment. In case of static environment, global Legendre pseudospectral method is employed for collision-free paths of vehicles for the purpose of minimum time consumption and simultaneous arrival. Moreover, in order to keep the multiple autonomous underwater vehicles safe from collisions on the path segments connecting two adjacent control nodes, an adaptive intermediate knots insertion algorithm is introduced. In the on-line planning stage, the local re-planning strategy aims at avoiding collisions with unexpected dynamic obstacles by two consecutive avoidance maneuvers, and the differential flatness property of autonomous underwater vehicle is utilized, which can help the vehicles react fast enough to avoid moving obstacles.

Keywords: Autonomous underwater vehicles (AUVs); Collision avoidance; Cooperative path planning; Differential flatness; Legendre pseudospectral method.