Artificial Immune System (AIS) is an excellent concept which is exploited in the field of Control Systems for the purpose of robot navigation. A number of algorithms has been developed over the years. The purpose of this research is to study the current algorithm and overcome shortcomings in obstacle detection phase. The thesis also focuses on integrating the SICK Laser Range Finder (LRF) with the existing immune algorithm. Robot navigation is closely associated with its localization in space and mapping the space in which the robot is present. Simultaneous Localization and Mapping (SLAM) this thesis is a supporting tool for visualizing robot path in space. This thesis aims to study the SLAM problem using Extended Kalman Filter (EKF) and implement it on Pioneer 3Dx along with the AIS navigation problem in C++.


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    Titel :

    SLAM and robot navigation using Artificial Immune System with speed variable obstacle detection


    Beteiligte:

    Erscheinungsdatum :

    01.05.2013


    Medientyp :

    Sonstige


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629



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