UAV Path Planning Under Multiple Threats Based on Improved Sparrow Search

In a complex environment, Unmanned Aerial Vehicles (UAVs) encounter multiple threats and require an optimal path to reach their destination. This paper proposes a probability distribution modeling method for threat areas and a point-selection solution method for UAV flight paths. Furthermore, the optimization index and constraint conditions of the path planning problem model are defined based on the specified requirements. To enhance the search capability of the original algorithm, an improved Sparrow Search algorithm is developed. This improvement focuses on correcting the location update strategy of discoverers and participants. The efficiency of the improved algorithm is demonstrated through comparative simulations.