@inproceedings{45b2256e486446f28bf915d7f5c5749c,
title = "Autonomous Unmanned Vehicle Automatic Visual Tracking Based on SLAM and YOLO Algorithm",
abstract = "In the UAV distribution center, the use of unmanned vehicles as the UAV carrier platform can perfectly compensate for the short time that UAVs are in the air, while saving manpower and material resources, autonomously completing navigation and obstacle avoidance in known environments, and at the same time. With human-computer interaction function, it provides target tracking ability, which greatly facilitates the centralized and distributed management of UAVs. In this paper, slam and yolo algorithms are utilized to implement automatic visual tracking of autonomous unmanned aerial vehicles (UAVs) and to achieve collaboration between UAVs and unmanned aerial vehicles (UAVs) in a known experimental environment.",
keywords = "Air-ground coordination, autonomous navigation and obstacle avoidance, target tracking",
author = "Xiaolei Qu and Jiaxing Wang and Xiulin Zhang and Xinyu Feng and Yang Du and Ke Li and Lijing Wang",
note = "Publisher Copyright: {\textcopyright} Beijing KeCui Man-Machine-Environment System Engineering Technology Research Academy 2024.; 24th Conference on Man-Machine-Environment System Engineering, MMESE 2024 ; Conference date: 18-10-2024 Through 20-10-2024",
year = "2024",
doi = "10.1007/978-981-97-7139-4\_73",
language = "英语",
isbn = "9789819771387",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "524--531",
editor = "Shengzhao Long and Dhillon, \{Balbir S.\} and Long Ye",
booktitle = "Man-Machine-Environment System Engineering - Proceedings of the 24th Conference on MMESE",
address = "德国",
}