• DocumentCode
    2717412
  • Title

    Identifying trajectory classes in dynamic tasks

  • Author

    Anderson, Stuart O. ; Srinivasa, Siddhartha S.

  • Author_Institution
    Robotics Inst., Carnegie Mellon Univ., Pittsburgh, PA
  • fYear
    2007
  • fDate
    1-5 April 2007
  • Firstpage
    172
  • Lastpage
    177
  • Abstract
    Using domain knowledge to decompose difficult control problems is a widely used technique in robotics. Previous work has automated the process of identifying some qualitative behaviors of a system, finding a decomposition of the system based on that behavior, and constructing a control policy based on that decomposition. We introduce a novel method for automatically finding decompositions of a task based on observing the behavior of a preexisting controller. Unlike previous work, these decompositions define reparameterizations of the state space that can permit simplified control of the system
  • Keywords
    robots; control problems; domain knowledge; dynamic tasks; robotics; system qualitative behaviors; trajectory classes; Automatic control; Control systems; Convergence; Dynamic programming; Humans; Learning; Motion control; Robot control; Robotics and automation; State-space methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Approximate Dynamic Programming and Reinforcement Learning, 2007. ADPRL 2007. IEEE International Symposium on
  • Conference_Location
    Honolulu, HI
  • Print_ISBN
    1-4244-0706-0
  • Type

    conf

  • DOI
    10.1109/ADPRL.2007.368185
  • Filename
    4220830