Key technologies of ship remote control system in inland waterways under ship-shore cooperation conditions
ObjectiveTo meet the requirements of remotely controlling ship in curved, narrow and crowded inland waterways, this paper proposes an approach that consists of CNN-based algorithms and knowledge based models under ship-shore cooperation conditions. MethodOn the basis of analyzing the characteristics...
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| Format: | Article |
| Language: | English |
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Editorial Office of Chinese Journal of Ship Research
2022-10-01
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| Series: | Zhongguo Jianchuan Yanjiu |
| Subjects: | |
| Online Access: | http://www.ship-research.com/cn/article/doi/10.19693/j.issn.1673-3185.02896 |
| _version_ | 1798023191970447360 |
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| author | Feng MA Chen CHEN Jialun LIU Xuming WANG Xinping YAN |
| author_facet | Feng MA Chen CHEN Jialun LIU Xuming WANG Xinping YAN |
| author_sort | Feng MA |
| collection | DOAJ |
| description | ObjectiveTo meet the requirements of remotely controlling ship in curved, narrow and crowded inland waterways, this paper proposes an approach that consists of CNN-based algorithms and knowledge based models under ship-shore cooperation conditions. MethodOn the basis of analyzing the characteristics of ship-shore cooperation, the proposed approach realizes autonomous perception of the environment with visual simulation at the core and navigation decision-making control based on deep reinforcement learning, and finally constructs an artificial intelligence system composed of image deep learning processing, navigation situation cognition, route steady-state control and other functions. Remote control and short-time autonomous navigation of operating ships are realized under inland waterway conditions, and remote control of container ships and ferries is carried out. ResultsThe proposed approach is capable of replacing manual work by remote orders or independent decision-making, as well as realizing independent obstacle avoidance, with a consistent deviation of less than 20 meters. ConclusionsThe developed prototype system carries out the remote control operation demonstration of the above ship types in such waterways as the Changhu Canal Shenzhou line and the Yangtze River, proving that a complete set of algorithms with a CNN and reinforcement learning at the core can independently extract key navigation information, construct obstacle avoidance and control awareness, and lay the foundation for inland river intelligent navigation systems. |
| first_indexed | 2024-04-11T17:42:16Z |
| format | Article |
| id | doaj.art-65d2480d933444a1892b05deea2514c1 |
| institution | Directory Open Access Journal |
| issn | 1673-3185 |
| language | English |
| last_indexed | 2024-04-11T17:42:16Z |
| publishDate | 2022-10-01 |
| publisher | Editorial Office of Chinese Journal of Ship Research |
| record_format | Article |
| series | Zhongguo Jianchuan Yanjiu |
| spelling | doaj.art-65d2480d933444a1892b05deea2514c12022-12-22T04:11:27ZengEditorial Office of Chinese Journal of Ship ResearchZhongguo Jianchuan Yanjiu1673-31852022-10-0117512513310.19693/j.issn.1673-3185.02896zg2896Key technologies of ship remote control system in inland waterways under ship-shore cooperation conditionsFeng MA0Chen CHEN1Jialun LIU2Xuming WANG3Xinping YAN4Intelligent Transport System Research Center, Wuhan University of Technology, Wuhan 430063, ChinaSchool of Computer Science and Technology, Wuhan Institute of Technology, Wuhan 430205, ChinaIntelligent Transport System Research Center, Wuhan University of Technology, Wuhan 430063, ChinaIntelligent Transport System Research Center, Wuhan University of Technology, Wuhan 430063, ChinaIntelligent Transport System Research Center, Wuhan University of Technology, Wuhan 430063, ChinaObjectiveTo meet the requirements of remotely controlling ship in curved, narrow and crowded inland waterways, this paper proposes an approach that consists of CNN-based algorithms and knowledge based models under ship-shore cooperation conditions. MethodOn the basis of analyzing the characteristics of ship-shore cooperation, the proposed approach realizes autonomous perception of the environment with visual simulation at the core and navigation decision-making control based on deep reinforcement learning, and finally constructs an artificial intelligence system composed of image deep learning processing, navigation situation cognition, route steady-state control and other functions. Remote control and short-time autonomous navigation of operating ships are realized under inland waterway conditions, and remote control of container ships and ferries is carried out. ResultsThe proposed approach is capable of replacing manual work by remote orders or independent decision-making, as well as realizing independent obstacle avoidance, with a consistent deviation of less than 20 meters. ConclusionsThe developed prototype system carries out the remote control operation demonstration of the above ship types in such waterways as the Changhu Canal Shenzhou line and the Yangtze River, proving that a complete set of algorithms with a CNN and reinforcement learning at the core can independently extract key navigation information, construct obstacle avoidance and control awareness, and lay the foundation for inland river intelligent navigation systems.http://www.ship-research.com/cn/article/doi/10.19693/j.issn.1673-3185.02896remote controlintelligent shipsautonomous navigationdeep reinforcement learningship-shore cooperation |
| spellingShingle | Feng MA Chen CHEN Jialun LIU Xuming WANG Xinping YAN Key technologies of ship remote control system in inland waterways under ship-shore cooperation conditions Zhongguo Jianchuan Yanjiu remote control intelligent ships autonomous navigation deep reinforcement learning ship-shore cooperation |
| title | Key technologies of ship remote control system in inland waterways under ship-shore cooperation conditions |
| title_full | Key technologies of ship remote control system in inland waterways under ship-shore cooperation conditions |
| title_fullStr | Key technologies of ship remote control system in inland waterways under ship-shore cooperation conditions |
| title_full_unstemmed | Key technologies of ship remote control system in inland waterways under ship-shore cooperation conditions |
| title_short | Key technologies of ship remote control system in inland waterways under ship-shore cooperation conditions |
| title_sort | key technologies of ship remote control system in inland waterways under ship shore cooperation conditions |
| topic | remote control intelligent ships autonomous navigation deep reinforcement learning ship-shore cooperation |
| url | http://www.ship-research.com/cn/article/doi/10.19693/j.issn.1673-3185.02896 |
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