The largest challenge observed in an autonomous robot is how the robot orients and adapts itself in an unknown environment or a terrain. An alternative solution to make the robot perform in the above condition in a desirable manner in its environment is implementing robot vision that enables the robot to observe. The scene segmentation algorithms is used to achieve a masking for various features in the scene and distinguishing the path from the obstacles thereby providing the robot with an understanding of the course by differentiating path and the probable obstacles. We propose a robot that can autonomously navigate and position itself in a room. The navigation is aided using deep neural techniques to segment the image while the positioning is taken care by the inbuilt IMU sensor that constantly keeps a track of the movement of the robot based on its x, y, z considering the robot emerged from its dock


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    Titel :

    Self Navigation and Positioning Robot - SNAPBot


    Beteiligte:
    Das, Amrit (Autor:in) / Giri, Rohan (Autor:in) / Chatterjee, Ayon (Autor:in) / Singh, Vanshika (Autor:in) / Dhanalakshmi, S. (Autor:in) / Kumar, R. (Autor:in)


    Erscheinungsdatum :

    2020-02-01


    Format / Umfang :

    929196 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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