Immune genetic algorithm based multi-UAV cooperative target search with event-triggered mechanism

In this paper, a strategy is designed to address the problem of closed trajectory cooperative target search for multiple UAVs, with the flight range and the initial and terminal heading constrains. The strategy is composed of two related phases, cooperative target searching phase and flight path planning phase for UAV returning to the nearest base. In the first phase, an Immune Genetic Algorithm (IGA) is proposed to improve the target search efficiency of UAVs in uncertain environment. An immune operator related to the problem is introduced to enhance the robustness of the algorithm, and expedite its convergent rate to the optimal solution. In the second phase, a Divide-and-conquer and Deterministic Path Optimization Algorithm (DDPOA) is designed to generate an optimal path for each UAV from the position of event trigger time instant to the nearest return base, with the initial and terminal velocity vector constraints. Simulations results verify the effectiveness of the algorithms.