Stratospheric airship trajectory planning in wind field using deep reinforcement learning-Reference-Cited by-同舟云学术

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Stratospheric airship trajectory planning in wind field using deep reinforcement learning

Published:2024-09 Issue: Volume: Page:
ISSN:0273-1177
Container-title:Advances in Space Research
language:en
Short-container-title:Advances in Space Research

Author:

Qi Lele,Yang Xixiang,Bai Fangchao,Deng Xiaolong,Pan Yuelong

Funder

National Natural Science Foundation of China

Key Research and Development Program of Hunan Province of China

Distinguished Young Scholar Foundation of Hunan Province

Hunan Provincial Natural Science Foundation

Construct Program of the Key Discipline in Hunan Province

Publisher

Elsevier BV

Reference29 articles.

1. Online path planning for autonomous airships in restricted environments;Alrashedi,2013

2. Araripe, D.F., De, M.F.C.L., Campos, D.T., 2016. High-altitude platforms — present situation and technology trends. J. Aerosp. Technol. Manag, 8(3), 249–262.

3. Autonomous navigation of stratospheric balloons using reinforcement learning;Bellemare;Nature,2020

4. Blouin, Charles, Lanteigne et al., 2016. Trajectory optimization of a small airship in a moving fluid. Trans. Canad. Soc. Mech. Eng.

5. Farley, R., 2005. Balloonascent: 3-d simulation tool for the ascent and float of high-altitude balloons. In: AIAA 5th ATIO and16th lighter-than-air sys tech. and balloon systems conferences, p. 7412.

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