An energy-saving path planning method using adaptive ant colony system for marine surface vehicles
Given the need for ship emission reduction and the energy constraints of unmanned surface vehicles, it is imperative to develop an efficient ship path planning method that incorporates energy-saving considerations. In this paper, considering the challenges posed by the complexity of the marine envir...
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| Vydáno v: | Soft computing (Berlin, Germany) Ročník 28; číslo 9-10; s. 6637 - 6656 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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Berlin/Heidelberg
Springer Berlin Heidelberg
01.05.2024
Springer Nature B.V |
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| ISSN: | 1432-7643, 1433-7479 |
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| Abstract | Given the need for ship emission reduction and the energy constraints of unmanned surface vehicles, it is imperative to develop an efficient ship path planning method that incorporates energy-saving considerations. In this paper, considering the challenges posed by the complexity of the marine environment, an adaptive ant colony system is proposed for ship energy-saving path planning. Firstly, a ship energy consumption estimation model is presented by analyzing the influence of wind, wave, and current on energy consumption. Secondly, two process evaluation indexes are designed for the quality and diversity of the paths in the optimization process. Based on these indexes, three improvements are presented to enhance the performance of the ant colony system. These improvements include (a) an adaptive state transition rule adjusted dynamically based on the information entropy, (b) the number of ants contributing to the global updating rule and the corresponding update value are controlled dynamically based on the quality of the path, and (c) an improved recombination mechanism. Besides, an improved turning point optimization method and B-spline curve are introduced for path post-processing. Finally, the effectiveness of the proposed method is verified by simulation experiments. |
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| AbstractList | Given the need for ship emission reduction and the energy constraints of unmanned surface vehicles, it is imperative to develop an efficient ship path planning method that incorporates energy-saving considerations. In this paper, considering the challenges posed by the complexity of the marine environment, an adaptive ant colony system is proposed for ship energy-saving path planning. Firstly, a ship energy consumption estimation model is presented by analyzing the influence of wind, wave, and current on energy consumption. Secondly, two process evaluation indexes are designed for the quality and diversity of the paths in the optimization process. Based on these indexes, three improvements are presented to enhance the performance of the ant colony system. These improvements include (a) an adaptive state transition rule adjusted dynamically based on the information entropy, (b) the number of ants contributing to the global updating rule and the corresponding update value are controlled dynamically based on the quality of the path, and (c) an improved recombination mechanism. Besides, an improved turning point optimization method and B-spline curve are introduced for path post-processing. Finally, the effectiveness of the proposed method is verified by simulation experiments. |
| Author | Dong, Liangxiong Gan, Xinhua |
| Author_xml | – sequence: 1 givenname: Liangxiong surname: Dong fullname: Dong, Liangxiong organization: School of Marine Engineering, Guangzhou Maritime University – sequence: 2 givenname: Xinhua orcidid: 0000-0001-5353-5912 surname: Gan fullname: Gan, Xinhua email: ganxinhua@zjou.edu.cn organization: School of Naval Architecture and Maritime, Zhejiang Ocean University |
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| SubjectTerms | Algorithms Application of Soft Computing Artificial Intelligence B spline functions Computational Intelligence Control Energy consumption Engineering Entropy (Information theory) Marine environment Mathematical Logic and Foundations Mechatronics Methods Optimization Path planning Performance indices Pheromones Planning Robotics Surface vehicles Unmanned vehicles Wind effects |
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