Predictive Control Strategy for AUV Docking with a Mobile Station and Co-Visibility Constraints

This paper address the problem of docking an Autonomous Underwater Vehicle (AUV) with a mobile docking station using Nonlinear Model Predictive Control (NMPC) strategy. The optimal control goal is to track the predicted motion of the docking station over the prediction horizon, instead of using only its current states. Further, co-visibility constraints are proposed to ensure that the docking station remains in the Field Of View (FOV) of the AUV and vice-versa. These constraints would allow the AUV and the Docking Station (DS) to use a vision-based localization in the terminal phases of docking operation. The performance of the proposed predictive strategy is illustrated through simulation.

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Publication Details

Published
2024-09-23
DOI
https://doi.org/10.1109/oceans55160.2024.10754106
Primary Topic
Underwater Vehicles and Communication Systems
Type
article
Field-Weighted Citation Impact
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article

Predictive Control Strategy for AUV Docking with a Mobile Station and Co-Visibility Constraints

Yuri Braz de Oliveira, Leizer Schnitman, R. Praveen Jain, Jérémy Nicola
Underwater Vehicles and Communication Systems
article

Predictive Control Strategy for AUV Docking with a Mobile Station and Co-Visibility Constraints

Yuri Braz de Oliveira, Leizer Schnitman, R. Praveen Jain, Jérémy Nicola
article en

Abstract

This paper address the problem of docking an Autonomous Underwater Vehicle (AUV) with a mobile docking station using Nonlinear Model Predictive Control (NMPC) strategy. The optimal control goal is to track the predicted motion of the docking station over the prediction horizon, instead of using only its current states. Further, co-visibility constraints are proposed to ensure that the docking station remains in the Field Of View (FOV) of the AUV and vice-versa. These constraints would allow the AUV and the Docking Station (DS) to use a vision-based localization in the terminal phases of docking operation. The performance of the proposed predictive strategy is illustrated through simulation.

Universidade Federal da Bahia (BR), Technology Innovation Institute (AE)
Openalex Percentile: Top 72%
Underwater Vehicles and Communication Systems
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