Open Access
Issue |
E3S Web Conf.
Volume 477, 2024
International Conference on Smart Technologies and Applied Research (STAR'2023)
|
|
---|---|---|
Article Number | 00077 | |
Number of page(s) | 12 | |
DOI | https://doi.org/10.1051/e3sconf/202447700077 | |
Published online | 16 January 2024 |
- B. Lee, S. Kwon, P. Park, and K. Kim, “Active power management system for an unmanned aerial vehicle powered by solar cells, a fuel cell, and batteries,” IEEE Trans. Aerosp. Electron. Syst., vol. 50, no. 4, pp. 3167 - 3177, 2014. [CrossRef] [Google Scholar]
- C. J. Salaan, Y. Okada, K. Hozumi, K. Ohno, and S. Tadokoro, “Improvement of UAV ’ s Flight Performance by Reducing the Drag Force of Spherical Shell,”vol. 2, no. 2, pp. 1708–1714, 2016. [Google Scholar]
- H. A. Kurdi et al., “Autonomous task allocation for multi-UAV systems based on the locust elastic behavior,” Appl. Soft Comput. J., vol. 71, pp. 110–126, 2018. [CrossRef] [Google Scholar]
- A. No, K. George, and G. Nikolakopoulos, “Science Direct Remaining Useful Battery Life Prediction for UAVs based Machine Learning for UAVs based on Machine Learning for UAVs based on Machine Learning,” IFAC-PapersOnLine, vol. 50, no. 1, pp. 4727–4732, 2017. [CrossRef] [Google Scholar]
- Li, Zhixiong, Kai Goebel, and Dazhong Wu. “Degradation modelling and remaining useful life prediction of aircraft engines using ensemble learning.” Journal of Engineering for Gas Turbines and Power 141.4 (2019): 041008. [CrossRef] [Google Scholar]
- P. Sarunic and R. Evans, “Hierarchical model predictive control of UAVs performing multitarget-multisensor tracking,” IEEE Trans. Aerosp. Electron. Syst., vol. 50, no. 3, pp. 2253–2268, 2014 [CrossRef] [Google Scholar]
- B. Lee, S. Kwon, P. Park, and K. Kim, “Active power management system for an unmanned aerial vehicle powered by solar cells, a fuel cell, and batteries,” IEEE Trans. Aerosp. Electron. Syst., vol. 50, no. 4, pp. 3167–3177, 2014. [CrossRef] [Google Scholar]
- T. Donateo, A. Ficarella, L. Spedicato, A. Arista, and M. Ferraro, “A new approach to calculating endurance in electric flight and comparing fuel cells and batteries,” Appl. Energy, vol.187,pp. 807–819, 2017. [CrossRef] [Google Scholar]
- A. Gautam, P. B. Sujit, and S. Saripalli, “Autonomous quadrotor landing using vision and pursuit guidance”. IFAC-PapersOnLine, 50(1), 10501-10506. [Google Scholar]
- A. Hiba, T. Zsedrovits, O. Heri, and A. Zarandy, “Runway detection for UAV landingsystem,” pp. 86–89, 2018. [Google Scholar]
- O. Araar, N. Aouf, and I. Vitanov, “Vision Based Autonomous Landing of Multirotor UAV on Moving Platform,” J. Intell. Robot. Syst., pp. 369–384, 2017. [Google Scholar]
- Kumar, Vijay, and Nathan Michael. “Opportunities and challenges with autonomous micro aerial vehicles.” The International Journal of Robotics Research 31.11 (2012): 1279-1291. [CrossRef] [Google Scholar]
- W. Du, J. Niu, M. Wang, J. Zhang, Y. Yang, and Y. Li, “An Analysis Model of Helicopter and UAV in Overhead Powerline Inspection,” IOP Conf. Ser. Earth Environ. Sci., vol. 189, no. 6,2018. [Google Scholar]
- Slimani, K., Khoulji, S., & Kerkeb, M. L. (2023). Advancements and challenges in energy-efficient 6G mobile communication network. In E3S Web of Conferences (Vol. 412, p. 01036). EDP Sciences. [Google Scholar]
- V. R. Sampath Kumar, M. Shanmugavel, V. Ganapathy, and B. Shirinzadeh, “Unified meta- modeling framework using bond graph grammars for conceptual modeling,” Rob. Auton. Syst., vol. 72, pp. 114–130, 2015. [CrossRef] [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.