Partial observability in EKF based mobile robot navigation is investigated in this paper to find a solution that can prevent erroneous estimation. By only considering certain landmarks in an environment, the computational cost in mobile robot can be reduced but with an increase of uncertainties to the system. This is known as suboptimal condition of the system. Fuzzy Logic technique is proposed to ensure that the estimation achieved desired performance even though some of the landmarks were excluded for references. The Fuzzy Logic is applied to the measurement innovation of Kalman Filter to correct the positions of both mobile robot and any observed landmarks during observations. The simulation results shown that the proposed method is capable to secure reliable estimation results even a number of landmarks being excluded from Kalman Filter update process in both Gaussian and non-Gaussian noise conditions.


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    Title :

    A Solution to Partial Observability in Extended Kalman Filter Mobile Robot Navigation


    Contributors:

    Publication date :

    2018-02-01


    Remarks:

    doi:10.12928/telkomnika.v16i1.9025
    TELKOMNIKA (Telecommunication Computing Electronics and Control); Vol 16, No 1: February 2018; 134-141 ; 2302-9293 ; 1693-6930 ; 10.12928/telkomnika.v16i1



    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629




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