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Record W3165280930 · doi:10.1016/j.cja.2021.04.022

A review on fault-tolerant cooperative control of multiple unmanned aerial vehicles

2021· review· en· W3165280930 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueChinese Journal of Aeronautics · 2021
Typereview
Languageen
FieldComputer Science
TopicDistributed Control Multi-Agent Systems
Canadian institutionsConcordia University
FundersState Key Laboratory of Synthetical Automation for Process IndustriesNatural Sciences and Engineering Research Council of CanadaNatural Science Foundation of Jiangsu ProvinceHigher Education Discipline Innovation ProjectNortheastern UniversityChina Postdoctoral Science FoundationKey Technologies Research and Development ProgramNational Natural Science Foundation of China
KeywordsFault toleranceControl (management)Collision avoidanceComputer scienceControl engineeringState (computer science)Distributed computingEngineeringFault (geology)CollisionArtificial intelligenceComputer security

Abstract

fetched live from OpenAlex

This paper presents the recent developments in Fault-Tolerant Cooperative Control (FTCC) of multiple unmanned aerial vehicles (multi-UAVs). To facilitate the analyses of FTCC methods for multi-UAVs, the formation control strategies under fault-free flight conditions of multi-UAVs are first summarized and analyzed, including the leader-following, behavior-based, virtual structure, collision avoidance, algebraic graph-based, and close formation control methods, which are viewed as the cooperative control methods for multi-UAVs at the pre-fault stage. Then, by considering the various faults encountered by the multi-UAVs, the state-of-the-art developments on individual, leader-following, and distributed FTCC schemes for multi-UAVs are reviewed in detail. Finally, conclusions and challenging issues towards future developments are presented.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.922
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.035
GPT teacher head0.321
Teacher spread0.286 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it