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Record W2154566430 · doi:10.1109/icsmc.1996.571315

Novel designs of a class of robust and dexterous end-effectors/fixtures for agile assembly

2002· article· en· W2154566430 on OpenAlexaff
Hong Miao, Shahram Payandeh

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRobot Manipulation and Learning
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsGRASPGrippersReconfigurabilityAgile software developmentHeuristicsComputer scienceFixtureModularity (biology)HeuristicFlexibility (engineering)EngineeringEngineering drawingArtificial intelligenceMechanical engineeringSoftware engineeringMathematics

Abstract

fetched live from OpenAlex

Agile assembly depends critically on flexible tooling including fixtures, feeders and end-effecters. There are many similarities in geometrical constraint and stability analysis between grasping and fixturing, so we treat them as one case concurrently. In this paper we present a class of novel designs of end-effecters and fixtures. Modularity, reconfigurability and reprogrammability will be a unifying trait of these novel designs. Compared with the parallel jaw grippers, our design has a rotary joint attached to each side of the grip jaw where some pegs are embedded. As a result, the grasp stability can be improved and the total grasp force can be reduced due to adding these constraint. The fixture consists of some blocks and a base. Those blocks can slide on each other, and move in order to clamp the workparts. It is enveloped and form closure in its structure. The planning algorithm is based on a generate and test paradigm. Candidate grasp configurations are generated using heuristics. The test phase involves checking each grasp configuration for force closure.

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 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 score0.848
Threshold uncertainty score0.284

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)0.0000.000

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 head0.066
GPT teacher head0.241
Teacher spread0.175 · 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

Citations5
Published2002
Admission routes1
Has abstractyes

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