FC-Planner: A Skeleton-guided Planning Framework for Fast Aerial Coverage of Complex 3D Scenes

被引:4
作者
Feng, Chen [2 ]
Li, Haojia [2 ]
Zhang, Mingjie [1 ]
Chen, Xinyi [2 ]
Zhou, Boyu [1 ]
Shen, Shaojie [2 ]
机构
[1] Sun Yat Sen Univ, Sch Artificial Intelligence, Zhuhai, Peoples R China
[2] Hong Kong Univ Sci & Technol, Dept Elect & Comp Engn, Hong Kong, Peoples R China
来源
2024 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, ICRA 2024 | 2024年
关键词
D O I
10.1109/ICRA57147.2024.10610621
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
3D coverage path planning for UAVs is a crucial problem in diverse practical applications. However, existing methods have shown unsatisfactory system simplicity, computation efficiency, and path quality in large and complex scenes. To address these challenges, we propose FC-Planner, a skeleton-guided planning framework that can achieve fast aerial coverage of complex 3D scenes without pre-processing. We decompose the scene into several simple subspaces by a skeleton-based space decomposition (SSD). Additionally, the skeleton guides us to effortlessly determine free space. We utilize the skeleton to efficiently generate a minimal set of specialized and informative viewpoints for complete coverage. Based on SSD, a hierarchical planner effectively divides the large planning problem into independent sub-problems, enabling parallel planning for each subspace. The carefully designed global and local planning strategies are then incorporated to guarantee both high quality and efficiency in path generation. We conduct extensive benchmark and real-world tests, where FC-Planner computes over 10 times faster compared to state-of-the-art methods with shorter path and more complete coverage. The source code will be made publicly available to benefit the community3. Project page: https://hkust-aerial-robotics.github.io/FC-Planner.
引用
收藏
页码:8686 / 8692
页数:7
相关论文
共 27 条
  • [1] Almadhoun R, 2018, IEEE INT C INT ROBOT, P7047, DOI 10.1109/IROS.2018.8593719
  • [2] [Anonymous], US
  • [3] Bircher A, 2015, IEEE INT CONF ROBOT, P6423, DOI 10.1109/ICRA.2015.7140101
  • [4] Blender, about us
  • [5] Cao C, 2020, IEEE INT CONF ROBOT, P3206, DOI [10.1109/ICRA40945.2020.9196575, 10.1109/icra40945.2020.9196575]
  • [6] A recursive greedy algorithm for walks in directed graphs
    Chekuri, C
    Pál, M
    [J]. 46TH ANNUAL IEEE SYMPOSIUM ON FOUNDATIONS OF COMPUTER SCIENCE, PROCEEDINGS, 2005, : 245 - 253
  • [7] Energy Efficient Path Planning for 3D Aerial Inspections
    Claro, Rafael M.
    Pereira, Maria I.
    Neves, Francisco S.
    Pinto, Andry M.
    [J]. IEEE ACCESS, 2023, 11 : 32152 - 32166
  • [8] SOLUTION OF A LARGE-SCALE TRAVELING-SALESMAN PROBLEM
    DANTZIG, G
    FULKERSON, R
    JOHNSON, S
    [J]. JOURNAL OF THE OPERATIONS RESEARCH SOCIETY OF AMERICA, 1954, 2 (04): : 393 - 410
  • [9] PredRecon: A Prediction-boosted Planning Framework for Fast and High-quality Autonomous Aerial Reconstruction
    Feng, Chen
    Li, Haojia
    Gao, Fei
    Zhou, Boyu
    Shen, Shaojie
    [J]. 2023 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, ICRA, 2023, : 1207 - 1213
  • [10] A survey on coverage path planning for robotics
    Galceran, Enric
    Carreras, Marc
    [J]. ROBOTICS AND AUTONOMOUS SYSTEMS, 2013, 61 (12) : 1258 - 1276