关键词: 双延迟深度确定性策略梯度（TD3）, 优先经验回放, 避障, 四旋翼无人机

Abstract:

In order to improve the intelligent obstacle avoidance performance of Unmanned Aerial Vehicle（UAV）, an improved algorithm called Improved Twin Delayed Deep Deterministic Policy Gradient（I-TD3）based on Twin Delayed Deep Deterministic Policy Gradient（TD3）is proposed. According to the different purposes of experience buffer pools, combined with the Prioritized Experience Replay and the Experience Replay, the success flight experience and failure flight experience are separated by setting two experience buffer pools to enhance the sample efficiency of effective experience, alleviate the problem of low training efficiency prompted by too much invalid experience. Meantime, the reward function is ameliorated to solve the problem of poor training effect caused by unreasonable reward setting. By applying the simulation experiment of quad-rotor UVA on AirSim platform, it is indicated that the obstacle avoidance effect of I-TD3 algorithm is superior to the TD3 algorithm and the Deep Deterministic Policy Gradient（DDPG） algorithm.

Key words: Twin Delayed Deep Deterministic Policy Gradient（TD3）, prioritized experience replay, obstacle avoidance, quad-rotor unmanned aerial vehicle