Multi-UAV Information Fusion and Cooperative Trajectory Optimization in Target Search
Peng Yao, Xin Wei
Abstract
With the increasing complexity of the search environment, it is particularly important for multiunmanned aerial vehicles (UAVs) to achieve a safe and efficient search for a dynamic target. For the communication network and information fusion among multi-UAVs, we adopt the minimum spanning tree structure as the communication network, and then based on this structure, the consensus algorithm with state predictor is utilized for the fusion of predicted target probability map. Moreover, based on the traditional model predictive control (MPC), the future-dependent MPC framework is proposed to realize the cooperative trajectory optimization and obtain the optimal control input, and especially the objective function of trajectory optimization is established by considering comprehensively the communication performance and the search performance. Finally, the feasibility of our method in the multi-UAV cooperative search task is verified via simulation.