• DocumentCode
    2772588
  • Title

    Development of learning control in robots

  • Author

    Su, Hu ; De Xu ; Huang, Yanlong

  • Author_Institution
    State Key Lab. of Intell. Control & Manage. of Complex Syst., Chinese Acad. of Sci., Beijing, China
  • fYear
    2011
  • fDate
    7-10 Aug. 2011
  • Firstpage
    433
  • Lastpage
    439
  • Abstract
    Learning control has been an active topic of research for several decades, and is of theoretical, as well as practical, significance. Current theories and developments in learning control are discussed. Following a brief introduction of the state as well as new progress on learning control, we give a detail review on the models and algorithms of the control policies developed recently which proved to be advantageous over previous approaches through experimental results. The related results and properties are presented. Then, several potentially developmental topics that are valuable to be further investigated are suggested. Finally, the conclusion remark is proposed.
  • Keywords
    learning (artificial intelligence); neurocontrollers; robots; active topic; control policy; learning control; robots; Data models; Heuristic algorithms; Hidden Markov models; Humans; Robot kinematics; Trajectory; Learning control; dynamic motor primitive; learn by imitation; locally weighted projection regress; locally weighted regress;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mechatronics and Automation (ICMA), 2011 International Conference on
  • Conference_Location
    Beijing
  • ISSN
    2152-7431
  • Print_ISBN
    978-1-4244-8113-2
  • Type

    conf

  • DOI
    10.1109/ICMA.2011.5985697
  • Filename
    5985697