The problem of 3D3D registration entails the estimation of spatial transformation which best aligns two point sets. Iterative Closest PointIterative Closest Point (ICP) is arguably the most popular and one of the most effective algorithms for 3D3D registration at present. This algorithm uses singular value decompositionDecomposition to obtain a least squares alignment of two point sets. As a greedy alignment procedure, Iterative Closest PointIterative Closest Point (ICP) is liable to converge to sub-optimal solutions. In this study, the problem of 3D3D registration is addressed using the popular Bees AlgorithmBees AlgorithmmetaheuristicsMetaheuristics. Thanks to its global searchGlobal Searchapproach, the Bees AlgorithmBees Algorithm, THE is known to be highly impervious to sub-optimal convergence. To increase the efficiency of the search, singular value decompositionDecomposition is used to exploit the search results of the BeesBees Algorithm. Experimental evidence showed that the proposed algorithm outperformed Iterative Closest PointIterative Closest Point (ICP) in terms of consistency and precision and showed high robustness to noiseNoise in the point sets.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Global Optimisation for Point Cloud Registration with the Bees Algorithm


    Weitere Titelangaben:

    Springer Ser.Advanced Manufacturing


    Beteiligte:
    Pham, Duc Truong (Herausgeber:in) / Hartono, Natalia (Herausgeber:in) / Lan, Feiying (Autor:in) / Castellani, Marco (Autor:in) / Wang, Yongjing (Autor:in) / Zheng, Senjing (Autor:in)


    Erscheinungsdatum :

    2022-11-20


    Format / Umfang :

    16 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Task Optimisation for a Modern Cloud Remanufacturing System Using the Bees Algorithm

    Caterino, Mario / Fera, Marcello / Macchiaroli, Roberto et al. | Springer Verlag | 2022




    Collaborative Optimisation of Robotic Disassembly Planning Problems using the Bees Algorithm

    Liu, Jiayi / Liu, Quan / Zhou, Zude et al. | Springer Verlag | 2022


    Global-PBNet: A Novel Point Cloud Registration for Autonomous Driving

    Zheng, Yuchao / Li, Yujie / Yang, Shuo et al. | IEEE | 2022