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Record W2079163206 · doi:10.1115/detc2003/vib-48500

Three Fingered Flexible Fixture Design

2003· article· en· W2079163206 on OpenAlexaff
Siamak Arzanpour, James K. Mills, William L. Cleghorn

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRobot Manipulation and Learning
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFixtureGRASPFlexibility (engineering)Mechanism (biology)ActuatorLinkage (software)Process (computing)GrippersComputer scienceControl reconfigurationEngineeringClampingWrenchSoftwareMechanical engineeringControl engineeringArtificial intelligenceEmbedded system

Abstract

fetched live from OpenAlex

Fixturing is an important requirement for many manufacturing and assembly operations. If flexible manufacturing and assembly system are to be truly flexible then the fixturing must also be flexible. A novel grasping strategy and gripper for fixturing in 3-D is presented for robotic assembly. The proposed fixture has three fingers, each equipped with a suction cup, to ease the grasping process and increase attaching flexibility. Using this method, the designed fixture is sufficiently general in order to fully grasp a variety of generic parts. To position suction cups, several linkage-based mechanisms are employed. Pneumatic cylinders and electrical motors are used as actuators to solve the space limitation and weight problem. Software has been developed to calculate the relative positions and angles in the mechanism as required for reconfiguration. A novel localization method is established to compensate for errors related to initial dislocation of the part due to low accuracy part bins from which parts are grasped. Several force and mechanism simulations are provided to verify the function and performance of the fixture.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.958
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

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)0.0020.000

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 head0.224
Teacher spread0.177 · 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.

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

Citations2
Published2003
Admission routes1
Has abstractyes

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