| 司鹏搏,吴兵,杨睿哲,李萌,孙艳华.基于DDPG三维无人机路径规划[J].高技术通讯(中文),2022,32(10):1049~1057 |
| 基于DDPG三维无人机路径规划 |
| A DDPG algorithm to UAV path planning in 3D |
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| DOI：10.3772/j.issn.1002-0470.2022.10.006 |
| 中文关键词: 无人机(UAV)；三维场景；路径规划；深度确定性策略梯度算法（DDPG）；避障 |
| 英文关键词: unmanned aerial vehicle (UAV), three-dimensional scene, path planning, deep deterministic policy gradient (DDPG), avoid obstacles |
| 基金项目: |
| 作者 | 单位 | | 司鹏搏 | (北京工业大学信息学部信息与通信工程学院北京 100124) | | 吴兵 | (北京工业大学信息学部信息与通信工程学院北京 100124) | | 杨睿哲 | (北京工业大学信息学部信息与通信工程学院北京 100124) | | 李萌 | (北京工业大学信息学部信息与通信工程学院北京 100124) | | 孙艳华 | (北京工业大学信息学部信息与通信工程学院北京 100124) |
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| 中文摘要: |
| 无人机(UAV)以其移动性高、环境适应能力强等优点，引起了广泛的关注，并被应用于军事和民用领域。本文研究了在复杂环境中，使用深度确定性策略梯度算法（DDPG）实现无人机路径规划。 首先，基于三维场景模型，将无人机任务过程划分为飞行、等待、通信阶段；其次，提出三维偏离度来表示无人机与障碍物及目标用户的相对位置，以提高无人机飞行和避障的有效性；最后，采用深度确定性策略梯度算法规划无人机的连续飞行动作，实现减少能量消耗、提高服务质量(QoS)，同时避开障碍、完成对用户数据传输的目的。通过仿真验证所提方案在各参数配置下的有效性，且优于现存算法。 |
| 英文摘要: |
| Unmanned aerial vehicles (UAVs) have attracted widespread attention due to their high mobility and strong environmental adaptability, and have been used in military and civilian fields. This work studies the method of using the deep deterministic policy gradient (DDPG) algorithm to achieve UAV path planning in complicated environment. Firstly, establish a three-dimensional scene model and divide the drone mission process into three stages: flight, waiting, and communication. Secondly, a three-dimensional deviation degree is proposed to indicate the relative position of the drone, obstacles and target users, so as to improve the flight performance of the drone and effectiveness of obstacle avoidance. Finally, the deep deterministic policy gradient algorithm is used to plan the continuous flight movements of the UAV to reduce energy consumption and improve the quality of service (QoS), while avoiding obstacles and completing data transmission to users. The simulation experimental results show that the proposed scheme is effective under various parameter configurations, and it is better than existing algorithms. |
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