"This book provides a novel perspective on secure state estimation and multimodal perception for robotic mobility platforms such as autonomous vehicles. In particular, the book discusses the two essential topics in autonomous systems: 1. secure state estimation that focuses on system robustness under cyber-attacks, and 2. multi-sensor fusion that helps improve system performance based on the complementary characteristics of different sensors. Finally, the authors introduce a geometric pose estimation framework to incorporate measurements and constraints into a unified fusion scheme, where real-time road-constrained and heading-assisted pose estimation is achieved. The proposed geometric pose estimation has been validated using public and self-collected data and can be further extended to other kinds of sensor configurations with state and measurement constraints."--


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    Titel :

    Multimodal perception and secure state estimation for robotic mobility platforms


    Beteiligte:
    Liu, Xinghua (Autor:in) / Jiang, Rui (Autor:in) / Chen, Badong (Autor:in) / Ge, Shuzhi Sam (Autor:in)

    Erscheinungsdatum :

    2023


    Format / Umfang :

    xvi, 208 Seiten


    Anmerkungen:

    Illustrationen, Diagramme
    Literaturverzeichnis: Seite 189-206



    Medientyp :

    Buch


    Format :

    Print


    Sprache :

    Englisch



    Klassifikation :

    BKL:    55.20 Straßenfahrzeugtechnik / 50.25 Robotertechnik
    DDC:    005.74



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