A control strategy of normal motion and active self-rescue for autonomous underwater vehicle based on deep reinforcement learning
Author:
Affiliation:
1. College of Power Engineering, Navy University of Engineering, Wuhan 430033, People’s Republic of China
2. National Key Laboratory on Ship Vibration and Noise, Naval University of Engineering, Wuhan 430033, People’s Republic of China
Funder
National Natural Science Foundation of China
Natural Science Foundation of Shandong Province
Independent Scientific Research Projects with Naval University of Engineering
Publisher
AIP Publishing
Subject
General Physics and Astronomy
Link
https://aip.scitation.org/doi/pdf/10.1063/5.0076857
Reference34 articles.
1. A. H. Sylvester, J. A. Delmerico, A. Z. Trimble, and B. S. Bingham, Variable buoyancy control for a bottom skimming autonomous underwater vehicle, 2014 Oceans, IEEE, St. John’s (2014), pp. 1–6.
2. L. Meng and Y. Qingyu, Enhanced safety control and self-rescue system applied in AUV, 2010 International Conference on Intelligent Computation Technology and Automation, IEEE, Changsha (2010), pp. 212–215.
3. Y. Putra, D. Gil Park, and K. WanChung, “Emergency path planning method for unmanned underwater robot,” in 2015 12th International Conference on Ubiquitous Robots and Ambient Intelligence (IEEE, Goyangi, 2015), pp. 242–245.
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