Abstract:

To improve the capability of multiple unmanned aerial vehicles (UAVs) for target searching and revising the region with high uncertainty,and then improve the effectiveness of multiple UAVs cooperative area target search, a multi-UAVs cooperative area target search method with controllable revisit to sub mission areas is presented. Firstly, an environment aware map that includes the target probability map, the uncertain map, the digital pheromone map and their calculating mechanisms are established. Secondly, considering the requirement of controllable revisiting to sub mission areas, a controllable revisiting mechanism is developed which is based on the characteristic of the pheromone, such as “secrete, propagate and evaporate”. This mechanism can control the UAVs to revisit sub mission areas with high target probability or maximum uncertainty. Thirdly, the optimizing functions based on the environment aware map are designed, in the frame of distributed receding horizon optimizing, a new decision making method for multi-UAVs cooperative area target search is established. The Monte Carlo method is employed to validate the impact of different number of UAV, sensing radius and sensor performance (sensor fidelity rate and false alarm rate) on the multi-UAVs cooperative area search. The simulation results prove that the controllable revisiting mechanism can guarantee the superior traversing ability, the revisiting ability and the target search efficiency.