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A novel fuzzy control path planning algorithm for intelligent ship based on scale factors

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Abstract

The melting of Arctic ice has increased the value of Arctic shipping, making research on the Arctic route a popular topic. However, ships navigating this route will likely encounter randomly distributed sea ice, which poses significant safety hazards to local path planning. The Dynamic Window Approach (DWA) is a suitable method for local path planning, but the DWA results in large ship rotation angles, increasing navigation risk. This study proposes a novel fuzzy control path planning algorithm based on scale factors to address this issue. The proposed algorithm combines a stability fuzzy controller with a collision risk controller to carry out adaptive control of DWA. Two scale factors are defined to improve fuzzy control based on the overall and obstacle avoidance phases. Results show that the proposed algorithm significantly reduces the rotation angle of DWA, improves the effect by 19.52%, shortens distance and time, and increases safety when encountering sea ice.

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Authors do not have permission to share the datasets used.

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Funding

This work was supported in part by the National Key Research and Development Program (Grant No. 2021YFC2801002), in part by the National Natural Science Foundation of China (Grant Nos. 52071200, 52201401, 52201403, and 52102397), in part by the Shanghai Committee of Science and Technology, China (Grant No. 23010502000), in part by the China Postdoctoral Science Foundation (Grant Nos. 2022M712027), in part by the Shanghai Post-doctoral Excellence Program (Grant No. 2022767), in part by the Top-Notch Innovative Program for Postgraduates of Shanghai Maritime University under Grant 2022YBR012, and in part by the Natural Science Foundation of Fujian Province under Grant 2022J01131710.

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Authors and Affiliations

  1. Merchant Marine College, Shanghai Maritime University, Shanghai, 201306, China

    Huafeng Wu, Feng Wang & Linian Liang

  2. College of Information Engineering, Shanghai Maritime University, Shanghai, 201306, China

    Xiaojun Mei & Dezhi Han

  3. Shanghai Ship and Shipping Research Institute Co. Ltd., Shanghai, 200135, China

    Bing Han

  4. Department of Computer Science and Information Engineering, Providence University, Taichung, 43301, Taiwan

    Tien-Hsiung Weng & Kuan-Ching Li

Authors
  1. Huafeng Wu
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  2. Feng Wang
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  3. Xiaojun Mei
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  4. Linian Liang
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  5. Bing Han
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  6. Dezhi Han
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  7. Tien-Hsiung Weng
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  8. Kuan-Ching Li
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Contributions

HW contributed to the methodology, writing—original draft preparation, and software; FW contributed to the conceptualization, methodology, writing—original draft preparation, resources, and software; LL was involved in the methodology, data curation, and resources; XM assisted in the resources, software, and validation; DH were involved in the methodology and supervision; K-CL contributed to the methodology, data curation, validation, visualization, supervision, and writing–reviewing and editing; T-HW performed the methodology, visualization, writing—reviewing and editing; BH contributed to writing—reviewing and editing.

Corresponding author

Correspondence to Tien-Hsiung Weng.

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Wu, H., Wang, F., Mei, X. et al. A novel fuzzy control path planning algorithm for intelligent ship based on scale factors. J Supercomput 80, 202–225 (2024). https://doi.org/10.1007/s11227-023-05438-2

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  • DOI: https://doi.org/10.1007/s11227-023-05438-2

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