• DocumentCode
    3107401
  • Title

    A Genetic Algorithm based area coverage approach for controlled drug delivery using micro-robots

  • Author

    Tao, WeiMin ; Zhang, Mingiuu ; Tarn, Tzyh-Jong

  • Author_Institution
    Brooks Autom. Inc., Mountain View, CA, USA
  • Volume
    2
  • fYear
    2004
  • fDate
    April 26-May 1, 2004
  • Firstpage
    2086
  • Abstract
    This paper describes a Genetic Algorithm (GA) based approach for area coverage using micro-robots. The method can be used for controlled drug delivery or tumor treatment using micro-robots. The algorithm aims to find a near-optimal path that covers a given area entirely, except obstacles defined as biological barriers or drug side effect restricted zones. The proposed GA approach is a dynamic online path planning approach, which is able to achieve planning during motion and to response to detected obstacles. Different from point-to-point path planning, the proposed operators for the GA are specially designed for area coverage. Comparisons of the approach with high-level static optimal search algorithms and low-level fixed path planning approaches are also presented. Simulation results are given to show the effectiveness of the approach.
  • Keywords
    drug delivery systems; genetic algorithms; medical robotics; microrobots; path planning; patient treatment; search problems; tumours; biological barriers; drug delivery; drug side effect; dynamic online path planning; genetic algorithm; microrobots; obstacles detection; point to point path planning; static optimal search algorithms; tumor treatment; Automatic control; Automation; Biological cells; Drug delivery; Genetic algorithms; Neoplasms; Optimal control; Paper technology; Path planning; Robot sensing systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics and Automation, 2004. Proceedings. ICRA '04. 2004 IEEE International Conference on
  • ISSN
    1050-4729
  • Print_ISBN
    0-7803-8232-3
  • Type

    conf

  • DOI
    10.1109/ROBOT.2004.1308131
  • Filename
    1308131