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https://hdl.handle.net/11147/14387
Title: | Open-Source Visual Target-Tracking System Both on Simulation Environment and Real Unmanned Aerial Vehicles | Authors: | Yılmaz,C. Ozgun,A. Erol,B.A. Gumus,A. |
Keywords: | Computer Vision ROS Sim2Real UAV Visual Target Tracking YOLOv7-Tiny |
Publisher: | Springer Science and Business Media Deutschland GmbH | Abstract: | This work presents an investigation into the domain of dynamic target tracking through object detection, particularly emphasizing the context of open-source applications like PX4, ROS, and YOLO. Over the years, achieving real-time object tracking on UAVs in dynamic environments has been a formidable challenge, necessitating offline computations or substantial onboard processing resources. However, contemporary UAVs are now equipped with advanced edge embedded devices, sensors, and cameras, enabling the integration of deep learning-based vision applications. This advancement offers the prospect of directly deploying cutting-edge applications onto UAVs, thereby expanding their utility in areas such as surveillance, search and rescue, and videography. To fully harness the potential of these vision applications, a communication infrastructure interfacing with the UAV’s underneath closed controllers becomes imperative. We’ve developed an integrated visual target-tracking system that connects a flight controller unit with a graphical unit by leveraging ROS tools and open-source deep learning packages. The overall integrated system based on ROS, deep learning applications, and custom PID controllers is shared on GitHub as open-source software package in a way that benefits everyone interested: https://github.com/miralab-ai/vision-ROS. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. | URI: | https://doi.org/10.1007/978-3-031-52760-9_11 https://hdl.handle.net/11147/14387 |
ISBN: | 978-303152759-3 | ISSN: | 2522-8595 |
Appears in Collections: | Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection |
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