• DocumentCode
    714114
  • Title

    Path planning for autonomous underwater vehicle based on artificial potential field and velocity synthesis

  • Author

    Chunlei Cheng ; Daqi Zhu ; Bing Sun ; Zhenzhong Chu ; Jianduo Nie ; Sheng Zhang

  • Author_Institution
    Lab. of Underwater Vehicles & Intell. Syst., Shanghai Maritime Univ., Shanghai, China
  • fYear
    2015
  • fDate
    3-6 May 2015
  • Firstpage
    717
  • Lastpage
    721
  • Abstract
    Because the impact of ocean current on Autonomous Underwater Vehicle (AUV) navigation is greater than the impact of wind on ground mobile robot, there is the essential difference between underwater environment and ground environment. Ocean current and obstacles must be considered for AUV path planning in underwater environment. In this paper, a novel kind of AUV path planning algorithm is proposed by combining the velocity synthesis algorithm and artificial potential field method. Firstly, the improved artificial potential field method is used to avoid obstacles effectively. Then according to the characteristics of AUV navigation, the velocity synthesis algorithm is used to achieve the optimal path. Finally, the problem of path planning for AUV in ocean current environment with obstacles is solved. Simulation result shows that the proposed algorithm is effective.
  • Keywords
    autonomous underwater vehicles; collision avoidance; mobile robots; navigation; AUV navigation; AUV navigation characteristics; AUV path planning algorithm; artificial potential field method; autonomous underwater vehicle; ground mobile robot; obstacle avoidance; ocean current environment; underwater environment; velocity synthesis algorithm; Force; Heuristic algorithms; Navigation; Oceans; Path planning; Robots; Underwater vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical and Computer Engineering (CCECE), 2015 IEEE 28th Canadian Conference on
  • Conference_Location
    Halifax, NS
  • ISSN
    0840-7789
  • Print_ISBN
    978-1-4799-5827-6
  • Type

    conf

  • DOI
    10.1109/CCECE.2015.7129363
  • Filename
    7129363