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.


    Access

    Download


    Export, share and cite



    Title :

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


    Contributors:

    Publication date :

    2015-01-19


    Remarks:

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



    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English


    Classification :

    DDC:    629






    Search and Rescue Robot Path Planning in Unknown Environment

    Pang, Tao ;Ruan, Xiao Gang ;Wang, Er Shen | Trans Tech Publications | 2012


    Path planning approach in unknown environment

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


    Mobile Robot Path Planning Based on Local Environment Modeling and Adaptive Window

    Zhong, Xun Yu ;Peng, Xia Fu ;Zhou, Jie Hua | Trans Tech Publications | 2011