Evidence map›Paper›PMID 42817252›Full record

ArticleSensors (Basel, Switzerland)2026

Risk-Aware Fault-Tolerant Multisensor Fusion for Human-Machine Decision Support in Autonomous Navigation and Mooring in Confined Waters.

Sergey I Kondratyev, Evgeniy V Khekert, Nikita V Martyushev, Boris V Malozyomov, Vladislav V Kukartsev, Valeriya V Tynchenko, Tatyana Aleksandrovna Panfilova, Yadviga Aleksandrovna Tynchenko, Natalia I Kozhukhova

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Sergey I KondratyevRector's Office, Admiral Ushakov Maritime State University, 93 Lenin Ave., Novorossiysk 353918, Russia.
Evgeniy V KhekertRector's Office, Admiral Ushakov Maritime State University, 93 Lenin Ave., Novorossiysk 353918, Russia.
Nikita V MartyushevDepartment of Information Technologies, Tomsk Polytechnic University, Tomsk 634050, Russia.ORCID 0000-0003-0620-9561
Boris V MalozyomovDepartment of Electrotechnical Complexes, Novosibirsk State Technical University, 20 Karl Marx Avenue, Novosibirsk 630073, Russia.ORCID 0000-0001-8686-9556
Vladislav V KukartsevDepartment of Software Engineering, Siberian Federal University, Krasnoyarsk 660041, Russia.
Valeriya V TynchenkoDepartment of Software Engineering, Siberian Federal University, Krasnoyarsk 660041, Russia.
Tatyana Aleksandrovna PanfilovaCenter for Continuing Education, Bauman Moscow State Technical University, Moscow 105005, Russia.
Yadviga Aleksandrovna TynchenkoCenter for Continuing Education, Bauman Moscow State Technical University, Moscow 105005, Russia.ORCID 0000-0001-8963-7830
Natalia I KozhukhovaDepartment of Material Science and Material Technology, Belgorod State Technological University Named After V.G. Shukhov, Belgorod 308012, Russia.ORCID 0000-0002-9380-0968

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Autonomous navigation and mooring in confined waters require a navigation solution that remains reliable when individual sensing channels are delayed, unavailable, or environmentally degraded. A risk- and integrity-aware architecture was developed for joint processing of RTK-GNSS, inertial and heading measurements, short-range radar, LiDAR, camera, AIS, ultrasonic ranging, propulsion feedback, environmental, and mooring-line tension data. Asynchronous time alignment is combined with sensor-quality assessment, innovation-based fault detection and isolation, covariance adaptation, active-set reconfiguration, protection-level monitoring, and risk-dependent allocation of authority between automation and the operator. The system was evaluated during a five-day campaign comprising 40 runs, four operational phases, 480 synchronized evaluation epochs, and 16 controlled single-sensor or combined sensor-degradation events. Under nominal conditions, horizontal-position and heading RMSE were 0.043 m and 0.176°, respectively. All 64 fault-active diagnostic records were identified; mean event-log detection and controlled-recovery latencies were 3.17 s and 6.34 s. Horizontal protection-level coverage was 99.3% for single-fault epochs and 100% for combined-fault epochs. One combined-fault docking run contained five consecutive aborted decision epochs, while no unsafe-autonomy event was recorded. The measurements therefore indicate bounded degradation of the navigation solution and conservative transfer of authority when sensing integrity decreases. Because all injected-fault runs were acquired under adverse weather whereas nominal runs were acquired under calm or moderate conditions, the condition-class RMSE differences reported below are descriptive and must not be interpreted as isolated causal effects of sensor faults.

Indexed as

autonomous mooringcomputer visionconfined watersfault detection and isolationGNSS/INS integrationheterogeneous sensor fusionhuman–machine decision supportLiDARmaritime radarnavigation integrity

Identifiers

PMID42817252
PMCPMC13611254

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.