• DocumentCode
    3404678
  • Title

    Grasp planning of 3D objects using genetic algorithm

  • Author

    Zhang, Zichen ; Gu, Jason

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Dalhousie Univ., Halifax, NS, Canada
  • fYear
    2012
  • fDate
    15-17 Aug. 2012
  • Firstpage
    646
  • Lastpage
    651
  • Abstract
    In this paper, we apply genetic algorithm (GA) to the optimization problem in grasp planning. This method can be used to find “pregrasps” for 3D objects in arbitrary shape and different dexterous hands, which serve as the first step of a complete grasping action. Each component of the GA planner is discussed in detail. The proposed algorithm is implemented in GraspIt! simulator [1]. It is tested on different hand-object combinations and the result shows that genetic algorithm is effective in finding high-quality pregrasps.
  • Keywords
    dexterous manipulators; genetic algorithms; object detection; robot vision; 3D objects; GA; arbitrary shape; dexterous hands; genetic algorithm; grasp planning; Biological cells; Genetic algorithms; Grasping; Optimization; Planning; Sociology; Statistics; Genetic Algorithm; Multifingered Hands; Robot Grasping;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automation and Logistics (ICAL), 2012 IEEE International Conference on
  • Conference_Location
    Zhengzhou
  • ISSN
    2161-8151
  • Print_ISBN
    978-1-4673-0362-0
  • Electronic_ISBN
    2161-8151
  • Type

    conf

  • DOI
    10.1109/ICAL.2012.6308157
  • Filename
    6308157