Abstract
This paper proposes a fast search algorithm based on points of interest for efficient multi-UAV collaborative area search. The algorithm utilizes a heatmap of the search area to identify subregions of interest and combines clustering algorithms and shortest path generation methods for integrated intra-subregion and inter-subregion exploration, considering UAV endurance. Moreover, the algorithm generates UAV search paths in “Full Coverage Search” or “Spiral Rectangle Search” patterns based on different task types, optimizing them using B-spline interpolation. Simulation results demonstrate the algorithm’s effectiveness in reducing search costs compared to random subregion allocation. The paper provides an integrated solution for search area and path planning in the field of multi-UAV collaborative search, enhancing search efficiency and optimizing UAV flight paths.
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Liu, J., Zou, D., Nan, X., Xia, X., Zhao, Z. (2024). Path Planning Algorithm for Multi-drone Collaborative Search Based on Points of Interest. In: Qu, Y., Gu, M., Niu, Y., Fu, W. (eds) Proceedings of 3rd 2023 International Conference on Autonomous Unmanned Systems (3rd ICAUS 2023). ICAUS 2023. Lecture Notes in Electrical Engineering, vol 1174. Springer, Singapore. https://doi.org/10.1007/978-981-97-1091-1_47
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DOI: https://doi.org/10.1007/978-981-97-1091-1_47
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