Abstract
Light and small UAVs have attracted widespread attention due to their good adaptability, low cost, and high temporal resolution. With the continuous development of technology, multi-UAV cooperation has become a research hot spot. The route planning problem of multi-UAV cooperation can be decomposed into two sub-problems: task allocation and route planning. In this paper, a task allocation method based on reinforcement learning is proposed for multi-UAV cooperation. Considering the task requirements, the capabilities of the UAV, the influence of the environment and the conflict of the task, we construct a MDP process include the state space, action space, reward function and discount factor with the constraints and optimization functions. In this paper, the task allocation process is combined with the trajectory planning based on maximizing information throughput, and a large number of simulation tests are carried out to verify the stability of the method.
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