Multi-UAV Cooperative Search Planning Algorithm Based on Dynamic Target Probability Model

This paper presents an online planning algorithm for multiple Unmanned Aerial Vehicles (UAVs) cooperative search tracks based on Distributed Model Predictive Control (DMPC) for dynamic targets. To address the centralized multiUAV collaboration problem, the proposed approach transforms it into a distributed subsystem MPC problem under the framework of DMPC. Firstly, a dynamic target Statistical Probability Map (SPM) update model is established. Next, the system optimal solution is obtained by combining Nash optimization and rolling optimization A-star algorithm through iterating the MPC problem of each subsystem. The simulation results demonstrate the efficacy of the proposed dynamic target SPM model in improving search efficiency. Furthermore, the scrolling-optimized A-star algorithm improves the accuracy and speed of subsystem single-step search. In conclusion, the DMPC method significantly reduces the solving scale of cooperative search problems while ensuring high solving accuracy.