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Research on Cooperative Collision Avoidance Problem of Multiple UAV Based on Reinforcement Learning

机译：基于强化学习的多无人机协同避碰问题研究

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摘要

To solve the problem of multi-UAV collision avoidance, propose the solution framework of multi-UAV collision avoidance based on the reinforcement learning. Firstly, four elements of state space, action space, the environment model and return value in the multi UAV cooperative collision avoidance problem were analyzed in depth. For the environment model, modeling it from two aspects of the UAV dynamic model and multi UAV relative distance calculation model; for the reward calculation, analyzing it from three aspects of the effect of collision avoidance, pre route deviation and maneuver execution cost. Then, proposing the multi UAV cooperative collision avoidance control algorithm based on the reinforcement learning. The experiment results show that the algorithm can effectively realize multi UAV coordination collision avoidance, control decision time is about 100 milliseconds, and the algorithm has practical feasibility.
机译：为解决多UAV避撞问题，提出了基于强化学习的多UAV避撞解决方案框架。首先，深入分析了多无人机协同避碰问题中的状态空间，动作空间，环境模型和返回值四个要素。对于环境模型，从无人机动态模型和多无人机相对距离计算模型两个方面进行建模。对于奖励计算，从避免碰撞的影响，预先路线偏离和机动执行成本三个方面进行分析。然后，提出了基于强化学习的多无人机协同防撞控制算法。实验结果表明，该算法可以有效地实现多无人机协同避撞，控制决策时间约为100毫秒，具有实际可行性。

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