Robust Cooperative Multi-UAV Search for Uncertain Targets
Yulong Dai, Yajie Dou, Ronghang Wang, Qingyang Jia, M.-J. Zhang, Biaobiao Qiu · 2023
A robust cooperative multiple unmanned aerial vehicles (UAVs) search method based on Bayesian theory is proposed for the multiple UAV cooperative area search problem. Firstly, based on the traditional rasterized map model, the environment model, state space model and sensor model of multiple UAV collaborative area search are established. Considering the uncertainty of UAV sensor measurements and the uncertainty of the environment itself, robustness performance parameters are introduced to improve the system’s anti-interference and stability. Then, based on the solution strategy of distributed model predictive control (DMPC), the centralized multiple UAV online optimization decision problem is transformed into a small-scale distributed optimization problem for each UAV. The particle swarm optimization (PSO) algorithm is used to solve the optimization problem iteratively for each UAV. The effectiveness of the proposed method is verified by simulation results.