A neuro-fuzzy network based approach for robot motion in an unknown environment was proposed. In order to control the robot motion in an unknown environment, the behavior of the robot was classified into moving to the goal and avoiding obstacles. Then, according to the dynamics of the robot and the behavior character of the robot in an unknown environment, fuzzy control rules were introduced to control the robot motion. At last, a 6-layer neuro-fuzzy network was designed to merge from what the robot sensed to robot motion control. After being trained, the network may be used for robot motion control. Simulation results show that the proposed approach is effective for robot motion control in unknown environment.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Realtime motion planning for a mobile robot in an unknown environment using a neurofuzzy based approach


    Contributors:

    Conference:

    ICMIT 2005: Control Systems and Robotics ; 2005 ; Chongqing,China


    Published in:

    Publication date :

    2005-12-22





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English







    DeepRL-Based Robot Local Motion Planning in Unknown Dynamic Indoor Environments

    Gonçalves, Gabriel / Palaio, Daniel / Garrote, Luís et al. | Springer Verlag | 2024