Learning Collaborative Multi-Target Search for A Visual Drone Swarm

In this paper, we propose a multi-agent reinforcement learning approach, POCA-Mix, to achieve collaborative multi-target search with a visual drone swarm. The proposed approach leverages the benefits of curriculum learning and mixed credit assignment to guide the drone swarm in per-forming the search task with only local visual perception in a constrained 3D environment. To validate the performance of the proposed approach, we conducted simulation experiments with various combinations regarding the number of drones and targets. The results demonstrate that the proposed approach outperforms other baseline methods such as PPO and MA-POCA with a higher success rate in different scenarios.