@inproceedings{01ad91d088024d3ea8d000e1c8d8a9bc,
title = "Target Detection and Positioning for UAV Search and Rescue in Complex Environments",
abstract = "UAVs have their unique advantages in agility and maneuverability, and thus been deployed in search and rescue missions. Visual information is a vital cue for target detection and positioning. However, in complex environments, targets might be occluded resulting in failure of detection and positioning using visual sensors. This paper presents a target detection and positioning algorithm for UAV search and rescue missions in complex environments. The proposed algorithm combines target detection and positioning with path planning to enable fast and robust search and rescue in presence of occluded targets. YoloV4 is used for target detection and depth information from RGBD sensor is invoked to derive target position. Path planning is incorporated to achieve good observation of targets with/without occluding obstacles. The effectiveness and real-time performance of the proposed algorithm was investigated via simulation study and flight experiments using a UAV platform.",
keywords = "Search and rescue, Target detection, Target positioning, UAV, Yolov4",
author = "Tao Jiang and Xiaolei Hou and Quan Pan",
note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; International Conference on Autonomous Unmanned Systems, ICAUS 2021 ; Conference date: 24-09-2021 Through 26-09-2021",
year = "2022",
doi = "10.1007/978-981-16-9492-9\_271",
language = "英语",
isbn = "9789811694912",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "2765--2776",
editor = "Meiping Wu and Yifeng Niu and Mancang Gu and Jin Cheng",
booktitle = "Proceedings of 2021 International Conference on Autonomous Unmanned Systems, ICAUS 2021",
}