A collaborative search planning method based on an information map is proposed for the problem of multi-moving target detection in gray areas using a heterogeneous UAV swarm. This method takes into account the detection probability and false alarm probability of sensors, the heterogeneity and flight constraints of UAVs, and the random movement of targets. The mathematical planning model for the collaborative search of multiple UAVs is built by balancing short-term gain, long-term gain, and coordination gain. An information map for search is designed, incorporating target existence probability, environmental uncertainty, and revisiting pheromones. Different planning schemes are designed based on the heterogeneous characteristics of UAVs. Through numerical simulations in typical collaborative search scenarios, the effectiveness of the proposed method is validated. The simulation results show that the proposed method can make search trajectory decisions for each UAV within seconds. The organic combination of short-term, long-term, and coordination gain can guide the UAV swarm to capture more targets. Comparative simulation results demonstrate that the proposed method can capture more targets with fewer false alarms, effectively improving the task efficiency of heterogeneous multi-UAV collaborative search.
Collaborative Search Method of Heterogeneous UAVs in Gray Area
Lect. Notes Electrical Eng.
Chinese Conference on Swarm Intelligence and Cooperative Control ; 2023 ; Nanjing, China November 24, 2023 - November 27, 2023
Proceedings of 2023 7th Chinese Conference on Swarm Intelligence and Cooperative Control ; Chapter : 2 ; 13-28
2024-06-18
16 pages
Article/Chapter (Book)
Electronic Resource
English
IEEE | 2014
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