A Particle Swarm Optimization-Based Cooperation Method for Multiple-Target Search by Swarm UAVs in Unknown Environments

This paper presents a decentralized method for multi-target search problem using a swarm of unmanned aerial vehicles with the information available from the onboard sensors. The proposed method deals with three main objectives: Time optimized multi-target search, optimized payload drops and inter-UAV collision avoidance which is independent of the number of UAVs. The proposed controller uses a modified Particle Swarm Optimization for cooperative multi-target search and is called Multi-Target Particle Swarm Optimization (MTPSO). The controller's performance is evaluated on Ardupilot's SITL platform for realistic simulations in various case-scenarios. Moreover, the performance of the controller with various inertial functions is also analyzed for different case-scenarios. Finally, the effectiveness of the proposed algorithm is illustrated by comparison with existing search methods.