Unmanned Aerial Vehicles Path Planning Based on Deep Reinforcement Learning-Reference-Cited by-同舟云学术

Unmanned Aerial Vehicles Path Planning Based on Deep Reinforcement Learning

Published:2019-11-07 Issue: Volume: Page:81-88
ISSN:2194-5357
Container-title:Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery
language:
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Author:

Wang Guoqiu,Zheng Xuanyu,Zhao Haitong,Zhao Qidong,Zhang Changsheng,Zhang Bin

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-32456-8_9

Reference17 articles.

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2. Yin, C., Xiao, Z., Cao, X., et al.: Offline and online search: UAV multiobjective path planning under dynamic urban environment. IEEE Internet Things J. 5(2), 546–558 (2018). https://doi.org/10.1109/JIOT.2017.2717078

3. Bevacqua, G., Cacace, J., Finzi, A., Lippiello, V.: Mixed-initiative planning and execution for multiple drones in search and rescue missions. In: Twenty-Fifth International Conference on Automated Planning and Scheduling. AAAI Publications (2015)

4. Chen, Y.B., Luo, G.C., Mei, Y.S., et al.: UAV path planning using artificial potential field method updated by optimal control theory. Int. J. Syst. Sci. 47(6), 1407–1420 (2016). https://doi.org/10.1080/00207721.2014.929191

5. Bortoff, S.A.: Path Planning for UAV. In: Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No. 00CH36334) (2000)

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