Lagrange tracking-based long-term drift trajectory prediction method for Autonomous Underwater Vehicle

Shuwen Zheng; Mingjun Zhang; Jing Zhang; Jitao Li; Shuwen Zheng; Mingjun Zhang; Jing Zhang; Jitao Li

doi:10.3934/mbe.2023932

Mathematical Biosciences and Engineering

2023, Volume 20, Issue 12: 21075-21097. doi: 10.3934/mbe.2023932

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Research article

Lagrange tracking-based long-term drift trajectory prediction method for Autonomous Underwater Vehicle

1.
College of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin 150001, China
2.
School of Information Science and Engineering, University of Jinan, Jinan 250022, China

Academic Editor: Hamid Reza Karim

Received: 27 August 2023 Revised: 20 November 2023 Accepted: 21 November 2023 Published: 27 November 2023

Autonomous Underwater Vehicle (AUV) works autonomously in complex marine environments. After a severe accident, an AUV will lose its power and rely on its small buoyancy to ascend at a slow speed. If the reserved buoyancy is insufficient, when reaching the thermocline, the buoyancy will rapidly decrease to zero. Consequently, the AUV will experience prolonged lateral drift within the thermocline. This study focuses on developing a prediction method for the drift trajectory of an AUV after a long-term power loss accident. The aim is to forecast the potential resurfacing location, providing technical support for surface search and salvage operations of the disabled AUV. To the best of our knowledge, currently, there is no mature and effective method for predicting long-term AUV underwater drift trajectories. In response to this issue, based on real AUV catastrophes, this paper studies the prediction of long-term AUV underwater drift trajectories in the cases of power loss. We propose a three-dimensional trajectory prediction method based on the Lagrange tracking approach. This method takes the AUV's longitudinal velocity, the time taken to reach different depths, and ocean current data at various depths into account. The reason for the AUV's failure to ascend to sea surface lies that the remaining buoyancy is too small to overcome the thermocline. As a result, AUV drifts long time within the thermocline. To address this issue, a method for estimating thermocline currents is proposed, which can be used to predict the lateral drift trajectory of the AUV within the thermocline. Simulation is conducted to compare the results obtained by the proposed method and that in a real accident. The results demonstrate that the proposed approach exhibits small directional and positional errors. This validates the effectiveness of the proposed method.
- AUV,
- underwater drift,
- lagrange tracking method,
- track prediction
Citation: Shuwen Zheng, Mingjun Zhang, Jing Zhang, Jitao Li. Lagrange tracking-based long-term drift trajectory prediction method for Autonomous Underwater Vehicle[J]. Mathematical Biosciences and Engineering, 2023, 20(12): 21075-21097. doi: 10.3934/mbe.2023932

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Abstract

Autonomous Underwater Vehicle (AUV) works autonomously in complex marine environments. After a severe accident, an AUV will lose its power and rely on its small buoyancy to ascend at a slow speed. If the reserved buoyancy is insufficient, when reaching the thermocline, the buoyancy will rapidly decrease to zero. Consequently, the AUV will experience prolonged lateral drift within the thermocline. This study focuses on developing a prediction method for the drift trajectory of an AUV after a long-term power loss accident. The aim is to forecast the potential resurfacing location, providing technical support for surface search and salvage operations of the disabled AUV. To the best of our knowledge, currently, there is no mature and effective method for predicting long-term AUV underwater drift trajectories. In response to this issue, based on real AUV catastrophes, this paper studies the prediction of long-term AUV underwater drift trajectories in the cases of power loss. We propose a three-dimensional trajectory prediction method based on the Lagrange tracking approach. This method takes the AUV's longitudinal velocity, the time taken to reach different depths, and ocean current data at various depths into account. The reason for the AUV's failure to ascend to sea surface lies that the remaining buoyancy is too small to overcome the thermocline. As a result, AUV drifts long time within the thermocline. To address this issue, a method for estimating thermocline currents is proposed, which can be used to predict the lateral drift trajectory of the AUV within the thermocline. Simulation is conducted to compare the results obtained by the proposed method and that in a real accident. The results demonstrate that the proposed approach exhibits small directional and positional errors. This validates the effectiveness of the proposed method.

References

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