A comparison of optimization techniques for AUV path planning in environments with ocean currents

Zheng Zeng, Karl Sammut, lian Lian, Fangpo He, Andrew Lammas, Youhong Tang

    Research output: Contribution to journalArticlepeer-review

    37 Citations (Scopus)

    Abstract

    To date, a large number of optimization algorithms have been presented for Autonomous Underwater Vehicle (AUV) path planning. However, little effort has been devoted to compare these techniques. In this paper, an quantum-behaved particle swarm optimization (QPSO) algorithm is introduced for solving the optimal path planning problem of an AUV operating in environments with ocean currents. An extensive study of the most important optimization techniques applied to optimize the trajectory for an AUV in several test scenarios is presented. Extensive Monte Carlo trials were also run to analyse the performance of these optimization techniques based on solution quality and stability. The weaknesses and strengths of each technique have been stated and the most appropriate algorithm for AUV path planning has been determined.

    Original languageEnglish
    Pages (from-to)61-72
    Number of pages12
    JournalROBOTICS AND AUTONOMOUS SYSTEMS
    Volume82
    DOIs
    Publication statusPublished - 1 Aug 2016

    Keywords

    • Autonomous underwater vehicle
    • Optimization
    • Path planning

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