In this paper, we propose a novel model-based coverage path planner for the 3D reconstruction of a target structure with an unmanned aerial vehicle (UAV). The proposed method rapidly calculates initial viewpoints considering the ground sampling distance (GSD) by partitioning a structure by height. Then, optimal viewpoints are selected by checking the collision and calculating overlaps and coverage. Next, the newly developed collision-aware Traveling Salesman Problem (CTSP) is used to connect the optimal viewpoints while guaranteeing the shortest distance and obstacle avoidance. Finally, the resulting path is refined as a control-efficient trajectory that considers the dynamics of UAVs. The performance of the proposed algorithm is verified by experiments on diverse structures.


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    Titel :

    CEO-MLCPP: Control-Efficient and Obstacle-Aware Multi-Layer Coverage Path Planner for 3D Reconstruction with UAVs


    Weitere Titelangaben:

    Lect. Notes in Networks, Syst.


    Beteiligte:
    Jo, Jun (Herausgeber:in) / Choi, Han-Lim (Herausgeber:in) / Helbig, Marde (Herausgeber:in) / Oh, Hyondong (Herausgeber:in) / Hwangbo, Jemin (Herausgeber:in) / Lee, Chang-Hun (Herausgeber:in) / Stantic, Bela (Herausgeber:in) / Lee, Eungchang Mason (Autor:in) / Jung, Sungwook (Autor:in) / Song, Seungwon (Autor:in) ... [mehr]

    Kongress:

    International Conference on Robot Intelligence Technology and Applications ; 2022 ; Daejeon, Korea (Republic of) December 07, 2022 - December 09, 2022



    Erscheinungsdatum :

    01.03.2023


    Format / Umfang :

    10 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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