• DocumentCode
    3499503
  • Title

    Problems of temporal granularity in robot control: Levels of adaptation and a necessity of self-confidence

  • Author

    Wagatsuma, Hiroaki ; Tomonaga, Yousuke

  • Author_Institution
    Dept. of Brain Sci. & Eng., Kyushu Inst. of Technol., Kitakyushu, Japan
  • fYear
    2011
  • fDate
    July 31 2011-Aug. 5 2011
  • Firstpage
    2670
  • Lastpage
    2675
  • Abstract
    The granularity of “action” within a system is highly depending on the internal representation for the task, or intention of what to do if it is a biological system. In the same time, there are several levels of adaptation when the system tries to complete a mission. The problem of choosing the right level of action representation is essential for robot controls as well as in learning paradigms. Both tend to use low-granularity and transfer the processed information to upper levels constructively. However the system never guarantees the completion time of the mission if the system is composed of stiff functional blocks with a specific temporal granularity at the bottom level. However, we biological system have an ability to manage the global time for scheduling and reorganization of tasks to finish by the deadline. Brain-inspired robotics allows us to investigate a distributed parallel information system, the brain, with the ability of time management as a real time control system of the physical body through flexible planning of necessary actions by interacting with the real environment. It is an extension of subsumption approaches that fixed a set of behaviors as the basic unit of action in the viewpoint of temporal property. By focusing on the temporal granularity as a consequence of coordination among multiple levels, a self-confident robot control may arise from a coupling between top-down or purpose-oriented decomposition of the purpose to primitive functions with flexible time windows and bottom-up of sensori-motor reactions in dynamic environments.
  • Keywords
    control engineering computing; learning (artificial intelligence); planning (artificial intelligence); real-time systems; robots; scheduling; biological system; brain-inspired robotics; distributed parallel information system; learning paradigms; planning; purpose-oriented decomposition; realtime control system; robot control; stiff functional blocks; task reorganization; task scheduling; time management; top-down decomposition; Cameras; Legged locomotion; Real time systems; Robot kinematics; Robot vision systems; Trajectory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks (IJCNN), The 2011 International Joint Conference on
  • Conference_Location
    San Jose, CA
  • ISSN
    2161-4393
  • Print_ISBN
    978-1-4244-9635-8
  • Type

    conf

  • DOI
    10.1109/IJCNN.2011.6033568
  • Filename
    6033568