Autonomously navigation of mobile robots in unknown environments is a basic challenge in robotics. We can use behavior based approach in navigation of mobile robots in environments with obstacles. If actions of robot be taken as behavior, we can design them by fuzzy logic. It decreases the problem states, make the navigation easier and also can be used as initial knowledge for reinforcement learning. In this paper we used learning automata for coordinating behaviors which caused robot to choose the best action in any situation. Using Pioneer robot in V-rep simulator environment showed that fuzzy logic and learning automata for robot navigation had a better performance in convergence and learning speed rather than fuzzy logic and Q-algorithm.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Mobile robots navigation in unknown environments by using fuzzy logic and learning automata


    Contributors:


    Publication date :

    2017-04-01


    Size :

    1188609 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Path Planning of Mobile Robots in Unknown Environments using Fuzzy Logic Based Hybrid Controller

    Mohanty, Prases K. / Singh, Anand Kumar / Kumar, Amit et al. | IEEE | 2021


    Some issues for mobile robots navigation under unknown environments

    Cai, Z.-x. / He, H.-g. / Chen, H. | British Library Online Contents | 2002



    Risk-Aware Navigation for Mobile Robots in Unknown 3D Environments

    Randriamiarintsoa, Elie / Laconte, Johann / Thuilot, Benoit et al. | IEEE | 2023


    Monocular vision-based navigation algorithm for mobile robots in unknown environments

    Qiang, Z. / Jia, W. | British Library Online Contents | 2008