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International Conference on Swarm Intelligence

ICSI 2018: Advances in Swarm Intelligence pp 132–141Cite as

Optimal Shape Design of an Autonomous Underwater Vehicle Based on Gene Expression Programming

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10942))

Abstract

A novel strategy combining gene expression programming and crowding distance based multi-objective particle swarm algorithm is presented in this paper to optimize an underwater robot’s shape. The gene expression programming method is used to establish the surrogate model of resistance and surrounded volume of the robot. After that, the resistance and surrounded volume are set as two optimized factors and Pareto optimal solutions are then obtained by using multi-objective particle swarm optimization. Finally, results are compared with the hydrodynamic calculations. Result shows the efficiency of the method proposed in the paper in the optimal shape design of an underwater robot.

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Acknowledgements

This work is supported by the project of National Natural Science Foundation of China (No. 61603277; No. 51579053; No. 61633009), the 13th-Five-Year-Plan on Common Technology, key project (No. 41412050101), the Shanghai Aerospace Science and Technology Innovation Fund (SAST 2016017). Meanwhile, this work is also partially supported by the Youth 1000 program project (No. 1000231901), as well as by the Key Basic Research Project of Shanghai Science and Technology Innovation Plan (No. 15JC1403300). All these supports are highly appreciated.

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Authors and Affiliations

  1. Laboratory of Robotics and Multibody System, School of Mechanical Engineering, Tongji University, Shanghai, 201804, People’s Republic of China

    Qirong Tang, Yinghao Li, Zhenqiang Deng, Di Chen & Ruiqin Guo

  2. National Key Laboratory of Science and Technology on Underwater Vehicle, Harbin Engineering University, Harbin, 150001, People’s Republic of China

    Hai Huang

Authors
  1. Qirong Tang
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  2. Yinghao Li
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  3. Zhenqiang Deng
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  4. Di Chen
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  5. Ruiqin Guo
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  6. Hai Huang
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Corresponding author

Correspondence to Qirong Tang .

Editor information

Editors and Affiliations

  1. Peking University, Beijing, China

    Ying Tan

  2. Southern University of Science and Technology, Shenzhen, China

    Yuhui Shi

  3. Tongji University, Shanghai, China

    Qirong Tang

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Tang, Q., Li, Y., Deng, Z., Chen, D., Guo, R., Huang, H. (2018). Optimal Shape Design of an Autonomous Underwater Vehicle Based on Gene Expression Programming. In: Tan, Y., Shi, Y., Tang, Q. (eds) Advances in Swarm Intelligence. ICSI 2018. Lecture Notes in Computer Science(), vol 10942. Springer, Cham. https://doi.org/10.1007/978-3-319-93818-9_13

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  • DOI: https://doi.org/10.1007/978-3-319-93818-9_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-93817-2

  • Online ISBN: 978-3-319-93818-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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