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Record W2518727019 · doi:10.1115/1.4034681

Switch-Based Sliding Mode Control for Position-Based Visual Servoing of Robotic Riveting System

2016· article· en· W2518727019 on OpenAlexaff
Zhao Yi, Yu Lin, Fengfeng Xi, Shuai Guo, P. R. Ouyang

Bibliographic record

VenueJournal of Manufacturing Science and Engineering · 2016
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Vision and Imaging
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsRivetRobotProcess (computing)EngineeringControl theory (sociology)Computer scienceStructural engineeringArtificial intelligenceControl (management)

Abstract

fetched live from OpenAlex

The robotic riveting system requires a rivet robotic positioning process for rivet-in-hole insertions, which can be divided into two stages: rivet path-following and rivet spot-positioning. For the first stage, varying parameter-linear sliding surfaces are proposed to achieve robust rivet path-following against robot errors and external disturbances of the robotic riveting system. For the second stage, a second-order sliding surface is applied to attain accurate rivet spot-positioning within a finite time required by the riveting process. In order to improve the dynamic performance of the robot riveting system, the motion of robot end-effector between the two adjacent riveting spots has been properly designed. Overall, the proposed control scheme can guarantee not only the stability of the robot control system but also the robust rivet path-following and quick rivet spot-positioning in the presence of the robot errors and external disturbances of the robotic riveting system. The simulation and experimental results demonstrate the effectiveness of the proposed control scheme.

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.

How this classification was reachedexpand

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.680
Threshold uncertainty score0.377

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.007
GPT teacher head0.240
Teacher spread0.234 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations24
Published2016
Admission routes1
Has abstractyes

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