Autonomous navigation strategies for mobile robots using a probabilistic neural network (PNN)

V. Castro, J. P. Neira, C. L. Rueda, J. C. Villamizar, L. Angel

    Research output: Chapter in Book/Report/Conference proceedingConference and proceedingspeer-review

    18 Scopus citations

    Abstract

    This paper presents a methodology for autonomous navigation of mobile robots with differential traction in poorly structured environments. The objective of die developed system is to navigate in areas with different types of obstacles could exist to go from one point to another without collision. The navigation methodology uses a Probabilistic Neuronal Network (PNN) as a decision core for control the motion of the mobile robot during its path. The methodology is implemented in the Optimus System, and the results obtained allow validate its performance.

    Original languageEnglish
    Title of host publicationProceedings of the 33rd Annual Conference of the IEEE Industrial Electronics Society, IECON
    Pages2795-2800
    Number of pages6
    DOIs
    StatePublished - 2007
    Event33rd Annual Conference of the IEEE Industrial Electronics Society, IECON - Taipei, Taiwan, Province of China
    Duration: 5 Nov 20078 Nov 2007

    Publication series

    NameIECON Proceedings (Industrial Electronics Conference)

    Conference

    Conference33rd Annual Conference of the IEEE Industrial Electronics Society, IECON
    Country/TerritoryTaiwan, Province of China
    CityTaipei
    Period5/11/078/11/07

    Fingerprint

    Dive into the research topics of 'Autonomous navigation strategies for mobile robots using a probabilistic neural network (PNN)'. Together they form a unique fingerprint.

    Cite this