Joint simultaneous localization and mapping (SLAM) constitutes the basis for cooperative action in multi-robot teams. We designed a stereo vision-based 6D SLAM system combining local and global methods to benefit from their particular advantages: (1) Decoupled local reference filters on each robot for real-time, long-term stable state estimation required for stabilization, control and fast obstacle avoidance; (2) Online graph optimization with a novel graph topology and intra- as well as inter-robot loop closures through an improved submap matching method to provide global multi-robot pose and map estimates; (3) Distribution of the processing of high-frequency and high-bandwidth measurements enabling the exchange of aggregated and thus compacted map data. As a result, we gain robustness with respect to communication losses between robots. We evaluated our improved map matcher on simulated and real-world datasets and present our full system in five real-world multi-robot experiments in areas of up 3,000 m2 (bounding box), including visual robot detections and submap matches as loop-closure constraints. Further, we demonstrate its application to autonomous multi-robot exploration in a challenging rough-terrain environment at a Moon-analogue site located on a volcano.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Distributed stereo vision-based 6D localization and mapping for multi-robot teams


    Beteiligte:


    Erscheinungsdatum :

    2018-10-17



    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Active Appearance-Based Robot Localization Using Stereo Vision

    Porta, J. M. / Verbeek, J. J. / Krose, B. J. | British Library Online Contents | 2005


    Night-vision stereo grid mapping for digital map localization

    Schule, Florian / Kramer, Marc Steven / Schweiger, Roland et al. | IEEE | 2014


    NIGHT-VISION STEREO GRID MAPPING FOR DIGITAL MAP LOCALIZATION

    Schule, F. / Kramer, M. / Schweiger, R. et al. | British Library Conference Proceedings | 2014


    Localization for Mobile Robot Teams: A Distributed MLE Approach

    Howard, Andrew / Matarić, Maja J. / Sukhatme, Gaurav S. | Springer Verlag | 2003