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Application of optimal control theory based on the evolution strategy (CMA-ES) to automatic berthing

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Abstract

To realize autonomous ships in the near future, possibility of automatic berthing has been investigated. Automatic berthing is not an easy task because of some complexities that are included in the problem, such as the nonlinearity of the low-speed maneuvering model, danger of collision with berth, etc. In this research, as a first step, the authors solved the off-line automatic berthing problem. Here, the optimal control problem was modeled as minimum-time problem, and the collision risk with the berth was taken into account. The authors attempted to apply the covariance matrix adaption evolution strategy (CMA-ES), which is considered state-of-the-art in evolutionary computation approaches for optimization of real-valued variables. In the problem dealt with here, a propeller and a rudder were used only as control inputs; so, the degree of difficulty was significantly high. Nevertheless, optimal control method based on the CMA-ES successfully gave us the offline results for typical situations considered. It is noteworthy that preparation of a feasible initial control input was not required in the calculation process, which made the proposed procedure robust. The calculation method proposed here is offline, but the results could be applied as an initial guess in an online (real-time) control problem.

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Acknowledgements

The authors are grateful to Mr. Koichi Shouji and Dr. Satoshi Masuda in JMU (Japan Marine United Corporation) for their technical advices and discussions. This work was supported by FY2018 Fundamental Research Developing Association for Shipbuilding and Offshore (REDAS) in Japan. The authors would like to thank Enago (http://www.enago.jp) for the English language review.

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Authors and Affiliations

  1. Department of Naval Architecture and Ocean Engineering, Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka, 565-0971, Japan

    Atsuo Maki, Hiroyuki Nishikawa & Naoya Umeda

  2. Graduate School of Medicine, Science and Technology, Shinshu University, 4-17-1 Wakasato, Nagano, Nagano, 380-8553, Japan

    Naoki Sakamoto

  3. Faculty of Engineering, Information and Systems, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8573, Japan

    Youhei Akimoto

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  1. Atsuo Maki
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  4. Hiroyuki Nishikawa
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  5. Naoya Umeda
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Correspondence to Atsuo Maki.

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Maki, A., Sakamoto, N., Akimoto, Y. et al. Application of optimal control theory based on the evolution strategy (CMA-ES) to automatic berthing. J Mar Sci Technol 25, 221–233 (2020). https://doi.org/10.1007/s00773-019-00642-3

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  • DOI: https://doi.org/10.1007/s00773-019-00642-3

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