Abstract A robot state estimation algorithm based on the vision feedback is proposed in the paper. The algorithm consists of an image feature detector and an extended Kalman filter (EKF) based estimator. The detected image features are scale-invariant and provide a robust representation of moving objects and static landmarks in the environment. The recursive EKF-based estimator is utilized to determine the pose and velocity of moving robots. Experiments are carried out on a hand-held binocular camera to verify the performances of the proposed state estimation algorithm. The results show that the integration of the image feature detector and the state estimator is efficient in highly dynamic environments.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Robot Pose and Velocity Estimation Using a Binocular Vision


    Beteiligte:
    Wang, Yin-Tien (Autor:in) / Wang, Shi-Hao (Autor:in) / Feng, Ying-Chieh (Autor:in) / Lin, Jin-Yi (Autor:in)


    Erscheinungsdatum :

    2011-01-01


    Format / Umfang :

    7 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Robot Pose and Velocity Estimation Using a Binocular Vision

    Wang, Y.-T. / Wang, S.-H. / Feng, Y.-C. et al. | British Library Conference Proceedings | 2011


    A Pose Estimation Method for Indoor UAV Based on Binocular Vision

    Jin, Ziqi / Zeng, Qinghua / Li, Yineng et al. | IEEE | 2023


    Pose Estimation for Vehicles Based on Binocular Stereo Vision in Urban Traffic

    Liu, Pengyu / Wang, Fei / He, Yicong et al. | British Library Conference Proceedings | 2015


    Binocular technical vision for wheeled robot controlling

    Anatoliy KULIK / Kostiantyn DERGACHOV / Oleksandr RADOMSKYI | DOAJ | 2015

    Freier Zugriff

    Bicycle cleaning robot based on binocular vision recognition

    WU XIRU / LIU BIAO / LIU JINXIA et al. | Europäisches Patentamt | 2023

    Freier Zugriff