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Cited by 257

The DOI matches its Crossref record; 53 of the 53 references it cites were found in a registry or an index.

Wireless Charging Techniques for UAVs: A Review, Reconceptualization, and Extension

Open access
Lu, Maxim, Bagheri, Mehdi, James, Alex P., Phung, Toan·2018·IEEE Access

Abstract

An important application in the growing field of unmanned aerial vehicles (UAVs) is in monitoring and inspection of high voltage power lines and electrical networks. The UAV-based monitoring method will save energy, simplify access to impassable or remote areas, reduce inspection cost, and automate the inspection process. However, the battery capacity of a medium scale drone limits their travel distance and mission duration. It is crucial to improve the energy feeding system of drones and overcome the battery capacity problem to foster the use of drones for routine monitoring operations. In this study, we focus on presenting wireless techniques available for drone mission duration improvement as well as discuss and practically examine the most feasible and reliable technique to charge UAV using power lines.

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Metadata

Authors
Lu, M., Bagheri, M., James, A. P., & Phung, T.
Venue
IEEE Access
Published
2018
Volume
6
Pages
29865-29884
ISSN
2169-3536 (ISSN-L)
OpenAlex
W2806940739
Cited by
257
References
53
FWCI
10.73
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Wireless Charging Techniques for UAVs: A Review, Reconceptualization, and Extension. https://app.cochat.ai/papers/10.1109/access.2018.2841376
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Lu, M., Bagheri, M., James, A. P., & Phung, T. (2018). Wireless Charging Techniques for UAVs: A Review, Reconceptualization, and Extension. IEEE Access. https://doi.org/10.1109/access.2018.2841376

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.