@inproceedings{92954f67d52b4ef69d3ccb99fa10f36a,
title = "Real-time obstacle avoidance with deep reinforcement learning* Three-Dimensional Autonomous Obstacle Avoidance for UAV",
abstract = "At present, drones are rapidly developing in the aviation industry and are applied to all aspects of life. However, letting drones autonomously avoid obstacles is still the focus of research by aviation scholars at this stage. However, the current automation is mostly based on human experience to determine the obstacle avoidance strategy of UAV. And the method only rely on the machine to avoid obstacle is very few. In this paper, the UAV collect visual and distance sensor information to make autonomous obstacle avoidance decision through the deep reinforcement learning algorithm, and the algorithm is tested in the v-rep simulation environment.",
keywords = "Aircraft, DQN, Obstacle avoidance, V-rep",
author = "Songyue Yang and Zhijun Meng and Xuzhi Chen and Ronglei Xie",
note = "Publisher Copyright: {\textcopyright} 2019 Association for Computing Machinery.; 2019 International Conference on Robotics, Intelligent Control and Artificial Intelligence, RICAI 2019 ; Conference date: 20-09-2019 Through 22-09-2019",
year = "2019",
month = sep,
day = "20",
doi = "10.1145/3366194.3366251",
language = "英语",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery ",
pages = "324--329",
booktitle = "Proceedings of the 2019 International Conference on Robotics, Intelligent Control and Artificial Intelligence, RICAI 2019",
address = "美国",
}