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    Statistical detection of faults in swarm robots under noisy conditions

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    CEIT18-ID-369.pdf
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    Type
    Conference Paper
    Authors
    Harrou, Fouzi cc
    Khaldi, Belkacem
    Sun, Ying cc
    Cherif, Foudil
    KAUST Department
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Statistics
    Statistics Program
    KAUST Grant Number
    CRG4-258
    Date
    2018-10
    Permanent link to this record
    http://hdl.handle.net/10754/656138
    
    Metadata
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    Abstract
    Fault detection plays an important role in supervising the operation of robotic swarm systems. If faults are not detected, they can considerably affect the performance of the robot swarm. In this paper, we present a robust fault detection mechanism against noise and uncertainties in data, by merging the multiresolution representation of data using wavelets with the sensitivity to small changes of an exponentially weighted moving average scheme. Specifically, to monitor swarm robotics systems performing a virtual viscoelastic control model for circle formation task, the proposed mechanism is applied to the uncorrelated residuals form principal component analysis model. Monitoring results using a simulation data from ARGoS simulator demonstrate that the proposed method achieves improved fault detection performances compared with the conventional approach.
    Citation
    Harrou, F., Khaldi, B., Sun, Y., & Cherif, F. (2018). Statistical detection of faults in swarm robots under noisy conditions. 2018 6th International Conference on Control Engineering & Information Technology (CEIT). doi:10.1109/ceit.2018.8751862
    Sponsors
    This publication is based upon work supported by the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Award No: OSR-2015-CRG4-2582. The work is done in collaboration with the LESIA Laboratory. Department of Computer Science, University of Mohamed Khider, Biskra, Algeria.
    Publisher
    Institute of Electrical and Electronics Engineers (IEEE)
    Conference/Event name
    2018 6th International Conference on Control Engineering & Information Technology (CEIT)
    DOI
    10.1109/CEIT.2018.8751862
    Additional Links
    https://ieeexplore.ieee.org/document/8751862/
    https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8751862
    ae974a485f413a2113503eed53cd6c53
    10.1109/CEIT.2018.8751862
    Scopus Count
    Collections
    Conference Papers; Statistics Program; Statistics Program; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

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