Accurate and robust vision-based pose estimation is essential for cooperative unmanned aerial vehicle (UAV) operations, particularly in formation flight and multi-UAV coordination, where precise relative positioning is critical to mission success. However, many existing systems rely on ac-tive sensors, limiting their applicability in environments with communication constraints, GNSS denial, or stealth require-ments. To overcome these limitations, recent studies have explored the use of passive sensors such as cameras. However, current methods, including marker-based and learning-based approaches, perform well under controlled conditions, but often struggle with viewpoint variability during dynamic maneuvers. To address these challenges, this paper presents the Viewpoint-Aware Pose Estimation (VAPE) framework, which enhances robustness across diverse viewpoints while operating with passive vision sensors. VAPE integrates viewpoint classification, robust feature matching using pre-trained models, and spatial feature distribution analysis to establish accurate 2D-3D correspondences without the need for specialized markers or extensive feature annotation. Ground tests simulating formation maneuvers demonstrate that VAPE maintains reliable tracking performance, achieving mean absolute position errors below 2.5 % and angular errors below 5°, indicating its potential for real-world UAV coordination tasks.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    VAPE: Viewpoint-Aware Pose Estimation Framework for Cooperative UAV Formation


    Beteiligte:
    Ryun, Kim Young (Autor:in) / Jung, Dongwon (Autor:in)


    Erscheinungsdatum :

    14.05.2025


    Format / Umfang :

    3529602 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Viewpoint-aware object detection and continuous pose estimation

    Glasner, D. / Galun, M. / Alpert, S. et al. | British Library Online Contents | 2012


    Cooperative Pose Estimation in a Robotic Swarm: Framework, Simulation and Experimental Results

    Zhang, Siwei / Cokona, Kimon / Pöhlmann, Robert et al. | Deutsches Zentrum für Luft- und Raumfahrt (DLR) | 2022

    Freier Zugriff


    Vision-based pose estimation for cooperative space objects

    Zhang, Haopeng | Online Contents | 2013


    Accurate Pose Estimation Based on Multi-frame Cooperative Identification

    Guo, JianPo / Dai, ZongMiao / Pan, WenTao | Springer Verlag | 2022