A Comprehensive Study of Data Fusion-Based Search and Path Planning for Submersibles


  • Liangchen Zhao
  • Xiao Yu
  • Juehui Shi




Underwater search and rescue, Logistic, Genetic algorithm, Circular search, QGIS.


With the increase in deep-sea exploration activities, the safety challenges faced by submersibles in complex marine environments have highlighted the importance and urgent need for search and rescue efforts. It is important to protect the marine environment and maintain the safety of personnel while minimizing economic losses. In this study, this paper predicted the wreck paths of submersibles by considering factors such as ocean currents, topography, and energy loss to obtain the wreck paths under different wreck scenarios. The rescue path of AUV equipment to the wrecked submersible is simulated using a genetic algorithm, which ensures that the search and rescue of the wrecked submersible is completed in a short period.


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How to Cite

Zhao, L., Yu, X., & Shi, J. (2024). A Comprehensive Study of Data Fusion-Based Search and Path Planning for Submersibles. Highlights in Science, Engineering and Technology, 105, 244-254. https://doi.org/10.54097/jgjsqs86