• DocumentCode
    506775
  • Title

    Underwater vehicle´s long voyage path planning in complex sea condition

  • Author

    Mao, Yufeng ; Pang, Yongjie ; Wang, Zhaoli

  • Author_Institution
    State Key Lab. of Autonomous Underwater Vehicle, Harbin Eng. Univ., Harbin, China
  • Volume
    2
  • fYear
    2009
  • fDate
    20-22 Nov. 2009
  • Firstpage
    661
  • Lastpage
    665
  • Abstract
    The characteristic of path planning for underwater vehicle is large planning area and sparse obstacles, effect of sea current. A new path planning approach in this paper is presented. In the method, trunk binary tree is used for environment modeling and search space generating so that planning area can be ignored. The heuristic evaluation function is designed by colligating path length, Ocean current and obstacles´ cost. A* heuristic evaluation arithmetic is used for getting the path by the least cost. Particle swarm optimization (PSO) in path planning is used for largely reducing disadvantage effect of ocean current and energy cost more. Simulation results prove the effectiveness of this approach which fulfills the demand of path planning for underwater vehicle.
  • Keywords
    marine control; particle swarm optimisation; path planning; trees (mathematics); underwater vehicles; complex sea condition; heuristic evaluation function; long voyage path planning; obstacles cost; ocean current; particle swarm optimization; trunk binary tree; underwater vehicle; Arithmetic; Automotive engineering; Binary trees; Cost function; Laboratories; Navigation; Oceans; Particle swarm optimization; Path planning; Underwater vehicles; A* arithmetic; component; ocean current; particle swarm optimization (PSO); trunk binary tree; underwater vehicle;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computing and Intelligent Systems, 2009. ICIS 2009. IEEE International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-4754-1
  • Electronic_ISBN
    978-1-4244-4738-1
  • Type

    conf

  • DOI
    10.1109/ICICISYS.2009.5358302
  • Filename
    5358302