• DocumentCode
    3453914
  • Title

    The essential visibility graph: an approach to global motion planning for autonomous mobile robots

  • Author

    Janét, Jason A. ; Luo, Ren C. ; Kay, Michael G.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., North Carolina State Univ., Raleigh, NC, USA
  • Volume
    2
  • fYear
    1995
  • fDate
    21-27 May 1995
  • Firstpage
    1958
  • Abstract
    An approach to global motion planning for autonomous mobile robots has been developed on the basis of traversability vectors (t-vectors). Through the overall course of this research it was found that t-vectors provide a utility, efficiency and mathematical stability for collision detection and visibility that cannot be matched by commonly used algebraic approaches in static and dynamic environments. This paper will show that t-vectors also impact global motion planning by identifying redundancies in visibility graphs (V-graphs) and expediting their construction. The result of eliminating redundant path segments is a streamlined version of the V-graph called the essential visibility graph (EVG). This paper will also show that the EVG offers a significant reduction in data storage requirements and complexity
  • Keywords
    computational complexity; graph theory; mobile robots; path planning; V-graph; autonomous mobile robots; collision detection; data storage requirements; efficiency; essential visibility graph; global motion planning; mathematical stability; redundancy identification; redundant path segments; t-vectors; traversability vectors; utility; Aerodynamics; Intelligent robots; Machine intelligence; Memory; Mobile robots; Motion planning; Robot sensing systems; Routing; Stability; Trajectory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics and Automation, 1995. Proceedings., 1995 IEEE International Conference on
  • Conference_Location
    Nagoya
  • ISSN
    1050-4729
  • Print_ISBN
    0-7803-1965-6
  • Type

    conf

  • DOI
    10.1109/ROBOT.1995.526023
  • Filename
    526023