Communication Outage-Resistant UUV State Estimation: A Variational History Distillation Approach

Fuente: arXiv
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Hauptverfasser: Li, Shuyue, López-Benítez, Miguel, Lim, Eng Gee, Ma, Fei, Dong, Qian, Cao, Mengze, Yu, Limin, Qin, Xiaohui
Format: Preprint
Veröffentlicht: 2026
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author Li, Shuyue
López-Benítez, Miguel
Lim, Eng Gee
Ma, Fei
Dong, Qian
Cao, Mengze
Yu, Limin
Qin, Xiaohui
author_facet Li, Shuyue
López-Benítez, Miguel
Lim, Eng Gee
Ma, Fei
Dong, Qian
Cao, Mengze
Yu, Limin
Qin, Xiaohui
contents The reliable operation of Unmanned Underwater Vehicle (UUV) clusters is highly dependent on continuous acoustic communication. However, this communication method is highly susceptible to intermittent interruptions. When communication outages occur, standard state estimators such as the Unscented Kalman Filter (UKF) will be forced to make open-loop predictions. If the environment contains unmodeled dynamic factors, such as unknown ocean currents, this estimation error will grow rapidly, which may eventually lead to mission failure. To address this critical issue, this paper proposes a Variational History Distillation (VHD) approach. VHD regards trajectory prediction as an approximate Bayesian reasoning process, which links a standard motion model based on physics with a pattern extracted directly from the past trajectory of the UUV. This is achieved by synthesizing ``virtual measurements'' distilled from historical trajectories. Recognizing that the reliability of extrapolated historical trends degrades over extended prediction horizons, an adaptive confidence mechanism is introduced. This mechanism allows the filter to gradually reduce the trust of virtual measurements as the communication outage time is extended. Extensive Monte Carlo simulations in a high-fidelity environment demonstrate that the proposed method achieves a 91% reduction in prediction Root Mean Square Error (RMSE), reducing the error from approximately 170 m to 15 m during a 40-second communication outage. These results demonstrate that VHD can maintain robust state estimation performance even under complete communication loss.
format Preprint
id arxiv_https___arxiv_org_abs_2603_29512
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Communication Outage-Resistant UUV State Estimation: A Variational History Distillation Approach
Li, Shuyue
López-Benítez, Miguel
Lim, Eng Gee
Ma, Fei
Dong, Qian
Cao, Mengze
Yu, Limin
Qin, Xiaohui
Robotics
Systems and Control
The reliable operation of Unmanned Underwater Vehicle (UUV) clusters is highly dependent on continuous acoustic communication. However, this communication method is highly susceptible to intermittent interruptions. When communication outages occur, standard state estimators such as the Unscented Kalman Filter (UKF) will be forced to make open-loop predictions. If the environment contains unmodeled dynamic factors, such as unknown ocean currents, this estimation error will grow rapidly, which may eventually lead to mission failure. To address this critical issue, this paper proposes a Variational History Distillation (VHD) approach. VHD regards trajectory prediction as an approximate Bayesian reasoning process, which links a standard motion model based on physics with a pattern extracted directly from the past trajectory of the UUV. This is achieved by synthesizing ``virtual measurements'' distilled from historical trajectories. Recognizing that the reliability of extrapolated historical trends degrades over extended prediction horizons, an adaptive confidence mechanism is introduced. This mechanism allows the filter to gradually reduce the trust of virtual measurements as the communication outage time is extended. Extensive Monte Carlo simulations in a high-fidelity environment demonstrate that the proposed method achieves a 91% reduction in prediction Root Mean Square Error (RMSE), reducing the error from approximately 170 m to 15 m during a 40-second communication outage. These results demonstrate that VHD can maintain robust state estimation performance even under complete communication loss.
title Communication Outage-Resistant UUV State Estimation: A Variational History Distillation Approach
topic Robotics
Systems and Control
url https://arxiv.org/abs/2603.29512