A Method of Multi-UAV Cooperative Task Assignment Based on Reinforcement Learning

Abstract

With the increasing complexity of UAV application scenarios, the performance of a single UAV cannot meet the mission requirements. Many complex tasks need the cooperation of multiple UAVs. How to coordinate UAV resources becomes the key to mission completion. In this paper, a task model including multiple UAVs and unknown obstacles is constructed, and the model is transformed into a Markov decision process (MDP). In addition, considering the influence of strategies among UAVs, a multiagent reinforcement learning algorithm based on SAC algorithm and centralized training and decentralized execution framework, MA-SAC (Multi-Agent Soft Actor-Critic), is proposed to solve the MDP. Simulation results show that the algorithm can effectively deal with the task allocation problem of multiple UAVs in this scenario, and its performance is better than other multiagent reinforcement learning algorithms.