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Ucgun H, Yuzgec U, Bayilmis C. A review on applications of rotary-wing unmanned aerial vehicle charging stations. INT J ADV ROBOT SYST 2021. [DOI: 10.1177/17298814211015863] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Today’s technology allows people to remotely control and monitor many systems. In these technological systems, robots or unmanned vehicles are generally used, which are controlled remotely without human interaction. Unmanned aerial vehicle (UAV), which does not have a pilot on it, is one of the unmanned vehicles capable of flying either remotely or automatically. UAVs are among the systems that are used in many fields for military, civil, and academic purposes and are constantly developing in parallel with the advancement of technology. One of the biggest problems of UAVs that are effectively used in many areas is undoubtedly flight times. To overcome this situation, charging stations are used and allow the UAV batteries to be charged without human intervention. In this article, a review study about the charging stations developed for charging batteries used in UAVs has been made. In this study, the findings obtained as a result of literature research on charging stations were analyzed and the performances of charging stations were compared. The main purpose of this review study is to guide people who will develop a charging station for rotary-wing UAVs by providing a preliminary research opportunity and to help choose one of the wired or wireless charging stations according to the needs in the applications to be developed.
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Affiliation(s)
- Hakan Ucgun
- Department of Computer and Information Engineering, Institute of Natural Sciences, Sakarya University, Sakarya, Turkey
| | - Ugur Yuzgec
- Department of Computer Engineering, Bilecik Seyh Edebali University, Bilecik, Turkey
| | - Cuneyt Bayilmis
- Department of Computer Engineering, Faculty of Computer and Information Sciences, Sakarya University, Sakarya, Turkey
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Liang J, Cai S, Xu C, Chu J. Filtering enhanced tomographic PIV reconstruction based on deep neural networks. IET CYBER-SYSTEMS AND ROBOTICS 2020. [DOI: 10.1049/iet-csr.2019.0040] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Affiliation(s)
- Jiaming Liang
- Institute of Cyber‐Systems and Control College of Control Science and Engineering Zhejiang University Hangzhou People's Republic of China
| | - Shengze Cai
- Institute of Cyber‐Systems and Control College of Control Science and Engineering Zhejiang University Hangzhou People's Republic of China
| | - Chao Xu
- Institute of Cyber‐Systems and Control College of Control Science and Engineering Zhejiang University Hangzhou People's Republic of China
| | - Jian Chu
- Institute of Cyber‐Systems and Control College of Control Science and Engineering Zhejiang University Hangzhou People's Republic of China
- Ningbo Industrial Internet Institute (NIII) Ningbo Zhejiang People's Republic of China
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