The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
A survey of quadrotor Unmanned Aerial Vehicles
Abstract
In the past decade Unmanned Aerial Vehicles (UAVs) have become a topic of interest in many research organizations. UAVs are finding applications in various areas ranging from military applications to traffic surveillance. This paper is a survey for a certain kind of UAV called quadrotor or quadcopter. Researchers are frequently choosing quadrotors for their research because a quadrotor can accurately and efficiently perform tasks that would be of high risk for a human pilot to perform. This paper encompasses the dynamic models of a quadrotor and the different model-dependent and model-independent control techniques and their comparison. Recently, focus has shifted to designing autonomous quadrotors. A summary of the various localization and navigation techniques has been given. Lastly, the paper investigates the potential applications of quadrotors and their role in multi-agent systems.
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Cites
A visual odometer for autonomous helicopter flight
Amidi, O., Kanade, T., & Fujita, K. (1999) · Robotics and Autonomous Systems · doi:10.1016/s0921-8890(99)00016-0 · Cited by 148
Cited by
Air-Ground Integrated Mobile Edge Networks: A Survey
Zhang, W., Li, L., Zhang, N., Han, T., & Wang, S. (2020) · IEEE Access · doi:10.1109/access.2020.3008168 · Cited by 75
Metadata
- Authors
- Gupte, S., Mohandas, P. I. T., & Conrad, J. M.
- Venue
- 2012 Proceedings of IEEE Southeastcon
- Publisher
- IEEE
- Published
- 2012-03
- Pages
- 1-6
- ISSN
- 1091-0050 (ISSN-L)
- OpenAlex
- W2025004307
- Cited by
- 389
- References
- 1
- FWCI
- 23.69
- Type
- conference paper
- Language
- en
- Open access
- closed
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- The paper
- Gupte, S., Mohandas, P. I. T., & Conrad, J. M. (2012). A survey of quadrotor Unmanned Aerial Vehicles. 2012 Proceedings of IEEE Southeastcon. https://doi.org/10.1109/secon.2012.6196930
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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.
