• DocumentCode
    2426500
  • Title

    Complete coverage algorithm based on linked smooth spiral paths for mobile robots

  • Author

    Lee, Tae-kyeong ; Baek, Sang-Hoon ; Oh, Se-young ; Choi, Young-Ho

  • Author_Institution
    Electron. & Electr. Eng. Dept., Pohang Univ. of Sci. & Technol. (POSTECH), Pohang, South Korea
  • fYear
    2010
  • fDate
    7-10 Dec. 2010
  • Firstpage
    609
  • Lastpage
    614
  • Abstract
    This paper presents an on-line complete-coverage path planning algorithm for mobile robots based on approximate cellular decomposition, which abstracts the target environment using grid. Most existing grid-based coverage algorithms have a common problem of constrained mobility which degrades the efficiency of the coverage task by inducing zigzag like path. In this paper, we propose a new complete coverage path generation algorithm, linked-smooth-spiral-path (LSSP), which removes the constraint on mobility by adopting a high-resolution grid-map representation of the environment and a cardinal-spline curve-model to generate a smooth spiral coverage path. We define a new performance measure for coverage tasks, which quantifies the smoothness of the coverage path. Simulation results demonstrate the improved coverage performance of the proposed algorithm compared to other existing grid-based coverage algorithms.
  • Keywords
    approximation theory; mobile robots; path planning; splines (mathematics); approximate cellular decomposition; cardinal-spline curve-model; complete coverage path generation algorithm; constrained mobility; grid-based coverage algorithms; high-resolution grid-map representation; linked smooth spiral paths; mobile robots; online complete-coverage path planning algorithm; zigzag like path; Algorithm design and analysis; Approximation algorithms; Mobile robots; Robot kinematics; Robot sensing systems; Spirals; coverage path planning; mobile robots; smooth spiral path;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Automation Robotics & Vision (ICARCV), 2010 11th International Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4244-7814-9
  • Type

    conf

  • DOI
    10.1109/ICARCV.2010.5707264
  • Filename
    5707264