Multiple fixed-wing UAVs collaborative coverage 3D path planning method for complex areas
Complex multi-area collaborative coverage path planning in dynamic environments poses a significant challenge for multi-fixed-wing UAVs (multi-UAV). This study establishes a comprehensive framework that incorporates UAV capabilities, terrain, complex areas, and mission dynamics. A novel dynamic coll...
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| Vydáno v: | Defence technology Ročník 47; s. 197 - 215 |
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| Hlavní autoři: | , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Elsevier B.V
01.05.2025
KeAi Communications Co., Ltd |
| Témata: | |
| ISSN: | 2214-9147, 2214-9147 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | Complex multi-area collaborative coverage path planning in dynamic environments poses a significant challenge for multi-fixed-wing UAVs (multi-UAV). This study establishes a comprehensive framework that incorporates UAV capabilities, terrain, complex areas, and mission dynamics. A novel dynamic collaborative path planning algorithm is introduced, designed to ensure complete coverage of designated areas. This algorithm meticulously optimizes the operation, entry, and transition paths for each UAV, while also establishing evaluation metrics to refine coverage sequences for each area. Additionally, a three-dimensional path is computed utilizing an altitude descent method, effectively integrating two-dimensional coverage paths with altitude constraints. The efficacy of the proposed approach is validated through digital simulations and mixed-reality semi-physical experiments across a variety of dynamic scenarios, including both single-area and multi-area coverage by multi-UAV. Results show that the coverage paths generated by this method significantly reduce both computation time and path length, providing a reliable solution for dynamic multi-UAV mission planning in semi-physical environments.
To address the optimization problem of complete coverage 3D path planning for multiple fixed-wing UAVs across multiple areas, this paper makes the following contributions:•Development of Models: Established models for UAV capabilities, terrain threats, complex areas, and mission optimization. The mission paths are categorized into three types based on the UAV field of view (FOV) status, forming a path optimization model.•Algorithmic Solutions: Utilized a greedy algorithm to solve the allocation problem between multi-UAV and multi-area. Introduced an improved dynamic programming algorithm to address the path optimization challenge when the UAV turn radius exceeds the FOV width. Employed an altitude descent algorithm to generate satisfactory 3D paths.•Validation and Adaptability: Validated the proposed methods through both digital and semiphysical simulations. The studies demonstrate that the methods effectively balance the trade-off between computation time and optimization, making them suitable for practical multi-UAV applications in dynamic scenarios.
These contributions ensure comprehensive path optimization, enhance the efficiency and effectiveness of multi-UAV operations, and support practical applications in complex and dynamic environments. |
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| ISSN: | 2214-9147 2214-9147 |
| DOI: | 10.1016/j.dt.2025.01.008 |