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Record W2126628059 · doi:10.1109/robot.1996.506513

Multi-robot control for flexible fixtureless assembly of flexible sheet metal auto body parts

2002· article· en· W2126628059 on OpenAlexaff
W. Nguyen, James K. Mills

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRobot Manipulation and Learning
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRobotSheet metalControl engineeringComputer scienceControl theory (sociology)UnobservableControl systemEngineeringControl (management)Mechanical engineeringArtificial intelligenceMathematics

Abstract

fetched live from OpenAlex

This paper addresses methods of control of a multi-robot system designed for the assembly of flexible sheet metal parts. The work begins with the dynamic modeling of two robots and their sheet metal payloads. Recognizing that the flexible sheet metal states are practically unobservable, since none of the sheet metal parts will be instrumented, a practical control algorithm is proposed based on the rigid body dynamics of the robot and payloads. Stability analysis is carried out using the theory of singularly perturbed dynamic systems to determine the effect of the "rigid" feedback on the flexible system. Experimental results are given to illustrate the dynamic response of the two robot system, while carrying out the assembly operation with the two robots under force control. The experiments are performed with two 6-DOF commercial industrial robots.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.046
GPT teacher head0.266
Teacher spread0.220 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations38
Published2002
Admission routes1
Has abstractyes

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