• DocumentCode
    2913143
  • Title

    Autonomous algorithms for terrain coverage metrics, classification and evaluation

  • Author

    Mason, Jonathan ; Menezes, Ronaldo

  • Author_Institution
    Dept. of Comput. Sci., Florida Inst. of Technol., Melbourne, FL
  • fYear
    2008
  • fDate
    1-6 June 2008
  • Firstpage
    1641
  • Lastpage
    1648
  • Abstract
    Terrain coverage algorithms are quite common in the computer science literature and for a good reason: they are able to deal with a diverse set of problems we face. From Web crawling to automated harvesting, from spell checking to area reconnaissance by unmanned aerial vehicles (UAVs), a good terrain coverage algorithm lies at the core of a successful approach to these and other problems. Despite the popularity of terrain coverage, none of the works in the field addresses the important issue of classification and evaluation of these algorithms. It is easy to think that all algorithms (since they are all called terrain coverage) deal with the same problem but this is a fallacy that this paper tries to correct. This paper presents a summary of many algorithms in the field, classifies them based on their goals, introduces metrics to evaluate them, and finally performs the evaluation.
  • Keywords
    path planning; robots; search problems; Web crawling; automated harvesting; autonomous control; classification; terrain coverage algorithms; unmanned aerial vehicles; Centralized control; Computer science; Helium; Lattices; Performance evaluation; Proposals; Reconnaissance; USA Councils; Unmanned aerial vehicles; Visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-1822-0
  • Electronic_ISBN
    978-1-4244-1823-7
  • Type

    conf

  • DOI
    10.1109/CEC.2008.4631011
  • Filename
    4631011