Real-time implementation of an online path replanner for an AUV operating in a dynamic and unexplored environment

被引：17

作者：

Lim, Hui Sheng ^{[1
]}

King, Peter ^{[1
]}

Chin, Christopher K. H. ^{[1
]}

Chai, Shuhong ^{[1
]}

Bose, Neil ^{[1
,2
]}

机构：

[1] Univ Tasmania, Australian Maritime Coll, Natl Ctr Maritime Engn & Hydrodynam, Launceston, Tas 7250, Australia

[2] Mem Univ Newfoundland, St John, NF A1C 5S7, Canada

来源：

APPLIED OCEAN RESEARCH | 2022年 / 118卷

基金：

澳大利亚研究理事会;

关键词：

Autonomous underwater vehicle; Path planning; Particle swarm optimization; Hardware-in-the-loop simulation; Real-time systems; PARTICLE SWARM OPTIMIZATION; ALGORITHM; VEHICLES; SYSTEM;

D O I：

10.1016/j.apor.2021.103006

中图分类号：

P75 [海洋工程];

学科分类号：

0814 ; 081505 ; 0824 ; 082401 ;

摘要：

This study describes the implementation of an online path planner in an autonomous underwater vehicle (AUV) system by using an open-source system architecture, MOOS-IvP. The path planner employed a path replanning scheme and the selective differential evolution quantum-behaved particle swarm optimization (SDEQPSO) algorithm. The implementation was based on a modular framework to ensure the robustness of the path replanner during a mission. The performance of the path replanner was evaluated and verified under stochastic processes hardware-in-the-loop (HIL) tests, in which the replanner interacted with the onboard controllers and actuators of an Explorer AUV. The experimental results showed the path replanner can be run seamlessly with the hardware onboard an Explorer AUV in real time to generate and continuously refine a safe and feasible path for a dynamic and unexplored environment.

引用

页数：14

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