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Unmanned Ship Path Planning Based on RRT

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Intelligent Computing Theories and Application (ICIC 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10954))

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Abstract

Path planning is a task of primary importance for unmanned ship, but current algorithms are complex and inefficient. In this paper, we propose a Rapidly-Exploring Random Tree algorithm (RRT) for path planning of unmanned ship, which can obtain an asymptotically optimal path planning in limited time. Moreover, an extension of RRT algorithm has been proposed to overcome the actual demand of multi-waypoint path planning for unmanned ship. The feasibility and effectiveness of the proposed algorithm was proved by simulation on MATLAB™ platform.

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References

  1. Zhu, D., Tian, C., Sun, B., et al.: Complete coverage path planning of autonomous underwater vehicle based on GBNN algorithm. J. Intell. Rob. Syst., 1–13 (2018)

    Google Scholar 

  2. Zhang Y.: Research on USV self-avoidance navigation control system based on artificial potential field. Hainan University (2017)

    Google Scholar 

  3. Zhuang, J., Wan, L., Liao, Y., et al.: Global path planning of unmanned watercraft based on electronic charts. Comput. Sci. 38(9), 211–214 (2011)

    Google Scholar 

  4. Chen, S., Liu, C., Huang, Z., et al.: AUV global path planning based on sparse A* algorithm. Torpedo Technol. 20(4), 271–275 (2012)

    Google Scholar 

  5. Zammit, C., Kampen, E.J.V.: Comparison between A* and RRT algorithms for UAV path planning. In: Aiaa Guidance, Navigation, and Control Conference (2018)

    Google Scholar 

  6. IHO: IHO Transfer Standard for Digital Hydrographic Data, 3.1 edn., Publication S-57. International Hydrographic Bureau, Monaco (2000)

    Google Scholar 

  7. Liu, Y., Bucknall, R.: Efficient multi-task allocation and path planning for unmanned surface vehicle in support of ocean operations. Neurocomputing 275, 1550–1566 (2018)

    Article  Google Scholar 

  8. Lavalle, S.M.: Rapidly-exploring random trees: a new tool for path planning. Algorithmic Comput. Rob. New Dir., 293–308 (1998)

    Google Scholar 

  9. LaValle, S.M.: Planning Algorithms. Cambridge University Press, Cambridge (2006)

    Book  Google Scholar 

  10. Du, Z., Wen, Y., Xiao, C., et al.: Motion planning for unmanned surface vehicle based on trajectory unit. Ocean Eng. 151(151), 46–56 (2018)

    Article  Google Scholar 

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Acknowledgement

Supported by Science and Technology Project of Guangdong Province, China (Granted No. 2017B010118002).

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Authors and Affiliations

  1. School of Software Engineering, South China University of Technology, Guangzhou, China

    Xinjia Chen & Yanxia Liu

  2. School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, China

    Xiaobin Hong, Xinyong Wei & Yesheng Huang

Authors
  1. Xinjia Chen
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  2. Yanxia Liu
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  3. Xiaobin Hong
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  4. Xinyong Wei
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  5. Yesheng Huang
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Corresponding author

Correspondence to Xiaobin Hong .

Editor information

Editors and Affiliations

  1. Tongji University, Shanghai, China

    De-Shuang Huang

  2. Polytechnic of Bari, Bari, Italy

    Vitoantonio Bevilacqua

  3. University of Wollongong, North Wollongong, New South Wales, Australia

    Prashan Premaratne

  4. Indian Institute of Technology Kanpur, Kanpur, India

    Phalguni Gupta

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Cite this paper

Chen, X., Liu, Y., Hong, X., Wei, X., Huang, Y. (2018). Unmanned Ship Path Planning Based on RRT. In: Huang, DS., Bevilacqua, V., Premaratne, P., Gupta, P. (eds) Intelligent Computing Theories and Application. ICIC 2018. Lecture Notes in Computer Science(), vol 10954. Springer, Cham. https://doi.org/10.1007/978-3-319-95930-6_11

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  • DOI: https://doi.org/10.1007/978-3-319-95930-6_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-95929-0

  • Online ISBN: 978-3-319-95930-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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