• DocumentCode
    1471910
  • Title

    Some Complexity Results for Metric View Planning Problem With Traveling Cost and Visibility Range

  • Author

    Wang, Pengpeng ; Gupta, Kamal ; Krishnamurti, Ramesh

  • Author_Institution
    RAMP Lab., Simon Fraser Univ., Burnaby, BC, Canada
  • Volume
    8
  • Issue
    3
  • fYear
    2011
  • fDate
    7/1/2011 12:00:00 AM
  • Firstpage
    654
  • Lastpage
    659
  • Abstract
    In this paper, we consider the problem where a point robot in a 2D or 3D environment equipped with an omnidirectional range sensor of finite range D is asked to cover a set of surface patches, while minimizing the sum of view cost, proportional to the number of viewpoints planned, and the travel cost, proportional to the length of path traveled. We call it the Metric View Planning Problem with Traveling Cost and Visibility Range or Metric TVPP in short. We present a complexity result for the problem, i.e., we show that the Metric TVPP cannot be approximated within O(log m) ratio by any polynomial algorithm, where m is the number of surface patches to cover. We then analyze a variant of an existing decoupled two-level algorithm of first solving the view planning problem to get an approximate solution, and then solving, again using an approximation algorithm, the Metric traveling salesman problem to connect the planned viewpoints. We then present performance bounds for this two-level decoupled algorithm, i.e., we show that it has an approximation ratio of O(log m). Thus, it asymptotically achieves the best approximation ratio one can hope for.
  • Keywords
    approximation theory; computational complexity; costing; mobile robots; path planning; polynomials; robot vision; sensors; travelling salesman problems; approximation algorithm; complexity; metric traveling salesman problem; metric view planning problem; omnidirectional range sensor; point robot; polynomial algorithm; surface patch; visibility range; Algorithm design and analysis; Approximation algorithms; Approximation methods; Measurement; Planning; Robot sensing systems; Approximation algorithms; approximation ratio; object modeling; view planning;
  • fLanguage
    English
  • Journal_Title
    Automation Science and Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1545-5955
  • Type

    jour

  • DOI
    10.1109/TASE.2011.2123888
  • Filename
    5730510