• DocumentCode
    147629
  • Title

    A genetic algorithm based approach to search optimal assembly sequences for autonomous robotic assembly

  • Author

    Qianli Zhao ; Jiayi Mu ; Feiling Yang ; Ting Li ; Ying Wang

  • Author_Institution
    Dept. of Electr. & Mechatron. Eng., Southern Polytech. State Univ., Marietta, GA, USA
  • fYear
    2014
  • fDate
    13-16 March 2014
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    A Genetic Algorithm (GA) based approach is proposed in this paper to search optimal assembly sequences in a robotic autonomous assembly task. In particular, the chromosome definition, the operations of crossover, copy and mutation and a specific fitness table are presented. Some simulation results are employed to validate the effectiveness of the proposed approach. The simulation results also indicate that the modified GA algorithm proposed in this paper has better performance than the traditional GA algorithm.
  • Keywords
    genetic algorithms; robotic assembly; autonomous robotic assembly; chromosome definition; genetic algorithm; optimal assembly sequences; Assembly; Biological cells; Genetic algorithms; History; Robotic assembly; Robots; Simulation; Autonomous Assembly; Genetic Algorithms; Robots;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    SOUTHEASTCON 2014, IEEE
  • Conference_Location
    Lexington, KY
  • Type

    conf

  • DOI
    10.1109/SECON.2014.6950735
  • Filename
    6950735