• DocumentCode
    1559297
  • Title

    A `retraction´ method for learned navigation in unknown terrains for a circular robot

  • Author

    Rao, Nageswara S V ; Stoltzfus, N. ; Iyengar, S.S.

  • Author_Institution
    Dept. of Comput. Sci., Old Dominion Univ., Norfolk, VA, USA
  • Volume
    7
  • Issue
    5
  • fYear
    1991
  • fDate
    10/1/1991 12:00:00 AM
  • Firstpage
    699
  • Lastpage
    707
  • Abstract
    The authors consider the problem of learned navigation of a circular robot R, of radius δ (⩾0), through a terrain whose model is not a priori known. The authors consider two-dimensional finite-sized terrains populated by an unknown (but finite) number of simple polygonal obstacles. The number and locations of the vertices of each obstacle are unknown to R; R is equipped with a sensor system that detects all vertices and edges that are visible from its present location. The authors deal with two problems: the visit problem and the terrain model acquisition problem. In the visit problem, the robot is required to visit a sequence of destination points, and in the terrain model acquisition problem, the robot is required to acquire the complete model of the terrain. The authors present an algorithmic network framework for solving these two problems based on a retraction of the free space onto the Voronoi diagram of the terrain
  • Keywords
    learning systems; navigation; planning (artificial intelligence); robots; Voronoi diagram; algorithmic network framework; circular robot; edges; learned navigation; machine learning; path planning; polygonal obstacles; sensor system; terrain model acquisition problem; vertices; visit problem; Computer applications; Computer science; Machining; Navigation; Orbital robotics; Path planning; Robot programming; Robot sensing systems; Robotics and automation; Service robots;
  • fLanguage
    English
  • Journal_Title
    Robotics and Automation, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1042-296X
  • Type

    jour

  • DOI
    10.1109/70.97883
  • Filename
    97883