Path Planning Method for AUV Docking Based on Adaptive Quantum-Behaved Particle Swarm Optimization

Path Planning Method for AUV Docking Based on Adaptive Quantum-Behaved Particle Swarm Optimization

AUV docking requires the platform to have both wide range cruising and accurate operating abilities, to against challenges of ocean currents, obstacles, and constraints. This paper proposed an evolutionary-based method, for the purpose of docking path optimization. First, the ocean environment and c...

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Bibliographic Details
Main Authors: Zeyu Li, Weidong Liu, Li-E Gao, Le Li, Feihu Zhang
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
AUV docking
path optimization
quantum behaved evolutionary algorithm
Online Access:https://ieeexplore.ieee.org/document/8736219/
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spelling doaj-7fe0c7a2ddd44fb596230a4c10af9dca2021-03-29T23:26:04ZengIEEEIEEE Access2169-35362019-01-017786657867410.1109/ACCESS.2019.29226898736219Path Planning Method for AUV Docking Based on Adaptive Quantum-Behaved Particle Swarm OptimizationZeyu Li0https://orcid.org/0000-0001-5593-8299Weidong Liu1Li-E Gao2Le Li3https://orcid.org/0000-0002-0412-7565Feihu Zhang4https://orcid.org/0000-0002-1774-727XSchool of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, ChinaSchool of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, ChinaSchool of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, ChinaSchool of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, ChinaSchool of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, ChinaAUV docking requires the platform to have both wide range cruising and accurate operating abilities, to against challenges of ocean currents, obstacles, and constraints. This paper proposed an evolutionary-based method, for the purpose of docking path optimization. First, the ocean environment and constraints are analyzed and modeled. Next, the control points are designed to satisfy the model constraints. Then, the adaptive law and quantum behavior are introduced in particle swarm optimization (PSO), to achieve global time-optimization. Finally, the proposed approach is evaluated via Monte-Carlo trials, which demonstrates a significant improvement with respect to the state-of-the-art approaches.https://ieeexplore.ieee.org/document/8736219/AUV dockingpath optimizationquantum behaved evolutionary algorithm
collection DOAJ
language English
format Article
sources DOAJ
author Zeyu Li
Weidong Liu
Li-E Gao
Le Li
Feihu Zhang
spellingShingle Zeyu Li
Weidong Liu
Li-E Gao
Le Li
Feihu Zhang
Path Planning Method for AUV Docking Based on Adaptive Quantum-Behaved Particle Swarm Optimization
IEEE Access
AUV docking
path optimization
quantum behaved evolutionary algorithm
author_facet Zeyu Li
Weidong Liu
Li-E Gao
Le Li
Feihu Zhang
author_sort Zeyu Li
title Path Planning Method for AUV Docking Based on Adaptive Quantum-Behaved Particle Swarm Optimization
title_short Path Planning Method for AUV Docking Based on Adaptive Quantum-Behaved Particle Swarm Optimization
title_full Path Planning Method for AUV Docking Based on Adaptive Quantum-Behaved Particle Swarm Optimization
title_fullStr Path Planning Method for AUV Docking Based on Adaptive Quantum-Behaved Particle Swarm Optimization
title_full_unstemmed Path Planning Method for AUV Docking Based on Adaptive Quantum-Behaved Particle Swarm Optimization
title_sort path planning method for auv docking based on adaptive quantum-behaved particle swarm optimization
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2019-01-01
description AUV docking requires the platform to have both wide range cruising and accurate operating abilities, to against challenges of ocean currents, obstacles, and constraints. This paper proposed an evolutionary-based method, for the purpose of docking path optimization. First, the ocean environment and constraints are analyzed and modeled. Next, the control points are designed to satisfy the model constraints. Then, the adaptive law and quantum behavior are introduced in particle swarm optimization (PSO), to achieve global time-optimization. Finally, the proposed approach is evaluated via Monte-Carlo trials, which demonstrates a significant improvement with respect to the state-of-the-art approaches.
topic AUV docking
path optimization
quantum behaved evolutionary algorithm
url https://ieeexplore.ieee.org/document/8736219/
work_keys_str_mv AT zeyuli pathplanningmethodforauvdockingbasedonadaptivequantumbehavedparticleswarmoptimization
AT weidongliu pathplanningmethodforauvdockingbasedonadaptivequantumbehavedparticleswarmoptimization
AT liegao pathplanningmethodforauvdockingbasedonadaptivequantumbehavedparticleswarmoptimization
AT leli pathplanningmethodforauvdockingbasedonadaptivequantumbehavedparticleswarmoptimization
AT feihuzhang pathplanningmethodforauvdockingbasedonadaptivequantumbehavedparticleswarmoptimization
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