research-article

Automatic path planning for autonomous underwater vehicles based on an adaptive differential evolution

Authors:

Chuan-Bin Zhang,

Ying LinAuthors Info & Claims

GECCO '14: Proceedings of the 2014 Annual Conference on Genetic and Evolutionary Computation

Pages 89 - 96

https://doi.org/10.1145/2576768.2598267

Published: 12 July 2014 Publication History

Abstract

This paper proposes a path planner for autonomous underwater vehicles (AUVs) in 3-D underwater space. We simulate an underwater space with rugged seabed and suspending obstacles, which is close to real world. In the proposed representation scheme, the problem space is decomposed into parallel subspaces and each subspace is described by a grid method. The paths of AUVs are simplified as a set of successive points in the problem space. By jointing these waypoints, the entire path of the AUV is obtained. A cost function with penalty method takes into account the length, energy consumption, safety and curvature constraints of AUVs. It is applied to evaluate the quality of paths. Differential evolution (DE) algorithm is used as a black-box optimization tool to provide optimal solutions for the path planning. In addition, we adaptively adjust the parameters of DE according to population distribution and the blockage of parallel subspaces so as to improve its performance. Experiments are conducted on 6 different scenarios. The results validate that the proposed algorithm is effective for improving solution quality and avoiding premature convergence.

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Cited By

Mohanty PChaudhary VPrajapati R(2024)Review on path planning methods for autonomous underwater vehicleProceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment10.1177/14750902241263250239:1(3-37)Online publication date: 8-Aug-2024
https://doi.org/10.1177/14750902241263250
Zhang XYang CGu ZTang CZhu ZZhang YQian JLi X(2023)Obstacle Avoidance for Trackless Rubber-Tired Vehicle Based on Risk-Grid Particle Swarm Optimization in Confined Space of Deep WellIEEE Transactions on Vehicular Technology10.1109/TVT.2023.327017472:9(11291-11303)Online publication date: Sep-2023
https://doi.org/10.1109/TVT.2023.3270174
Gong YHuang TMa YJeon SZhang J(2023)MTrajPlanner: A Multiple-Trajectory Planning Algorithm for Autonomous Underwater VehiclesIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2023.323493724:4(3714-3727)Online publication date: Apr-2023
https://doi.org/10.1109/TITS.2023.3234937
Show More Cited By

Index Terms

Automatic path planning for autonomous underwater vehicles based on an adaptive differential evolution
1. Computing methodologies
  1. Artificial intelligence
    1. Control methods
    2. Search methodologies
2. Theory of computation
  1. Design and analysis of algorithms
    1. Algorithm design techniques
      1. Dynamic programming

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cover image ACM Conferences

GECCO '14: Proceedings of the 2014 Annual Conference on Genetic and Evolutionary Computation

July 2014

1478 pages

ISBN:9781450326629

DOI:10.1145/2576768

Editor-in-chief:
Christian Igel
Ruhr University of Bochum, University of Copenhagen
,
General Chair:
Dirk V. Arnold
Dalhousie University

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 July 2014

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GECCO '14

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SIGEVO

GECCO '14: Genetic and Evolutionary Computation Conference

July 12 - 16, 2014

BC, Vancouver, Canada

Acceptance Rates

GECCO '14 Paper Acceptance Rate 180 of 544 submissions, 33%;

Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Citations

Cited By

Mohanty PChaudhary VPrajapati R(2024)Review on path planning methods for autonomous underwater vehicleProceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment10.1177/14750902241263250239:1(3-37)Online publication date: 8-Aug-2024
https://doi.org/10.1177/14750902241263250
Zhang XYang CGu ZTang CZhu ZZhang YQian JLi X(2023)Obstacle Avoidance for Trackless Rubber-Tired Vehicle Based on Risk-Grid Particle Swarm Optimization in Confined Space of Deep WellIEEE Transactions on Vehicular Technology10.1109/TVT.2023.327017472:9(11291-11303)Online publication date: Sep-2023
https://doi.org/10.1109/TVT.2023.3270174
Gong YHuang TMa YJeon SZhang J(2023)MTrajPlanner: A Multiple-Trajectory Planning Algorithm for Autonomous Underwater VehiclesIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2023.323493724:4(3714-3727)Online publication date: Apr-2023
https://doi.org/10.1109/TITS.2023.3234937
Sun SSong BWang PDong HChen X(2022)Real-Time Mission-Motion Planner for Multi-UUVs Cooperative Work Using Tri-Level ProgramingIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2020.302381923:2(1260-1273)Online publication date: Feb-2022
https://doi.org/10.1109/TITS.2020.3023819
Jin KZhuo HXiao ZWan HKambhampati S(2022)Gradient-Based Mixed Planning with Symbolic and Numeric Action ParametersArtificial Intelligence10.1016/j.artint.2022.103789(103789)Online publication date: Sep-2022
https://doi.org/10.1016/j.artint.2022.103789
Cheng CSha QHe BLi G(2021)Path planning and obstacle avoidance for AUV: A reviewOcean Engineering10.1016/j.oceaneng.2021.109355235(109355)Online publication date: Sep-2021
https://doi.org/10.1016/j.oceaneng.2021.109355
Han GZhou ZZhang TWang HLiu LPeng YGuizani M(2020)Ant-Colony-Based Complete-Coverage Path-Planning Algorithm for Underwater Gliders in Ocean Areas With ThermoclinesIEEE Transactions on Vehicular Technology10.1109/TVT.2020.299813769:8(8959-8971)Online publication date: Aug-2020
https://doi.org/10.1109/TVT.2020.2998137
Yu XChen WHu XGu TYuan HZhou YZhang J(2020)Path Planning in Multiple-AUV Systems for Difficult Target Traveling Missions: A Hybrid Metaheuristic ApproachIEEE Transactions on Cognitive and Developmental Systems10.1109/TCDS.2019.294494512:3(561-574)Online publication date: Sep-2020
https://doi.org/10.1109/TCDS.2019.2944945
Panda MDas BSubudhi BPati B(2020)A Comprehensive Review of Path Planning Algorithms for Autonomous Underwater VehiclesInternational Journal of Automation and Computing10.1007/s11633-019-1204-9Online publication date: 4-Jan-2020
https://doi.org/10.1007/s11633-019-1204-9
Ma YGong YXiao CGao YZhang J(2019)Path Planning for Autonomous Underwater Vehicles: An Ant Colony Algorithm Incorporating Alarm PheromoneIEEE Transactions on Vehicular Technology10.1109/TVT.2018.288213068:1(141-154)Online publication date: Jan-2019
https://doi.org/10.1109/TVT.2018.2882130
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