Now-a-days autonomous mobile robots have found applications in diverse fields. An autonomous robot system must be able to behave in an intelligent manner to deal with complex and changing environment. This work proposes the performance of path planning and navigation of autonomous mobile robot using Gravitational Search Algorithm (GSA), Simulated Annealing (SA) and Particle Swarm optimization (PSO) based intelligent controllers in an unstructured environment. The approach not only finds a valid collision free path but also optimal one. The main aim of the work is to minimize the length of the path and duration of travel from a starting point to a target while moving in an unknown environment with obstacles without collision. Finally, a comparison is made between the three controllers, it is found that the path length and time duration made by the robot using GSA is better than SA and PSO based controllers for the same work.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Comparison of GSA, SA and PSO Based Intelligent Controllers for Path Planning of Mobile Robot in Unknown Environment


    Beteiligte:
    P. K. Panigrahi (Autor:in) / Saradindu Ghosh (Autor:in) / Dayal R. Parhi (Autor:in)

    Erscheinungsdatum :

    19.01.2015


    Anmerkungen:

    oai:zenodo.org:1337859
    International Journal of Electrical, Electronic and Communication Sciences 7.0(10)



    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch


    Klassifikation :

    DDC:    629






    Path planning approach in unknown environment

    Wang, T. K. / Dang, Q. / Pan, P. Y. | British Library Online Contents | 2010


    PATH FOLLOWING IN UNKNOWN ENVIRONMENT FOR A CAR-LIKE MOBILE ROBOT

    Ruangpayoongsak, N. / Roth, H. / Institute for Systems and Technologies for Information, Control and Communication et al. | British Library Conference Proceedings | 2005


    Research on Path Planning of Mobile Robot Based on Dynamic Environment

    Cheng, Zhixiang / Li, Bin / Liu, Bin | British Library Conference Proceedings | 2022