• DocumentCode
    617902
  • Title

    Robot path planning in an environment with many terrains based on interval multi-objective PSO

  • Author

    Na Geng ; Dunwei Gong ; Yong Zhang

  • Author_Institution
    Sch. of Inf. & Electr. Eng., China Univ. of Min. & Technol., Xuzhou, China
  • fYear
    2013
  • fDate
    20-23 June 2013
  • Firstpage
    813
  • Lastpage
    820
  • Abstract
    In order to solve the problem of path planning in an environment with many terrains, we propose a method based on interval multi-objective Particle Swarm Optimization (PSO). First, the environment is modeled by the line partition method, and then, according to the distribution of the polygonal lines which form the robot path and taking the velocity´s disturbance into consideration, robot´s passing time is formulated as an interval by combining Local Optimal Criterion (LOC), and the path´s danger degree is estimated through the area ratio between the robot path and the danger source. In addition, the path length is also calculated as an optimization objective. As a result, the robot path planning problem is modeled as an optimization problem with three objectives. Finally, the interval multiobjective PSO is employed to solve the problem above. Simulation and experimental results verify the effectiveness of the proposed method.
  • Keywords
    mobile robots; particle swarm optimisation; path planning; LOC; interval multiobjective PSO; line partition method; local optimal criterion; particle swarm optimization; path danger degree; polygonal line distribution; robot passing time; robot path planning problem; terrain; velocity disturbance; Educational institutions; Evolutionary computation; Mathematical model; Optimization; Path planning; Robot kinematics; interval multi-objective optimization; many terrains; mobile robot; particle swarm optimization; path planning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation (CEC), 2013 IEEE Congress on
  • Conference_Location
    Cancun
  • Print_ISBN
    978-1-4799-0453-2
  • Electronic_ISBN
    978-1-4799-0452-5
  • Type

    conf

  • DOI
    10.1109/CEC.2013.6557652
  • Filename
    6557652