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Record W2069888278 · doi:10.1163/156855307780108231

Management of parallel-manipulator singularities using joint-coupling

2007· article· en· W2069888278 on OpenAlexaff
Theingi, I‐Ming Chen, Jorge Angeles, Chuan Li

Bibliographic record

VenueAdvanced Robotics · 2007
Typearticle
Languageen
FieldEngineering
TopicRobotic Mechanisms and Dynamics
Canadian institutionsMcGill University
Fundersnot available
KeywordsGravitational singularityParallel manipulatorJoint (building)Manipulator (device)Coupling (piping)Computer scienceRobotRobot manipulatorControl engineeringControl theory (sociology)EngineeringArtificial intelligenceMechanical engineeringStructural engineeringMathematicsControl (management)Mathematical analysis

Abstract

fetched live from OpenAlex

Joint-coupling (JC) is introduced in the design and control of parallel manipulators for managing manipulator singularities. The underlying idea consists of coupling the motions of several manipulator joints by driving the joints with a single actuator. This can be done by mechanical or electronic means, while preserving the mobility of the manipulator. Such JC is intended to alter the direct singularity condition of parallel manipulators upon changing the coupling coefficients. Both 2- and 3-d.o.f. planar parallel manipulator examples are provided to illustrate the concept of JC and singularity management. The prototype of a JC device and its associated 2-d.o.f. parallel manipulator intended for a feasibility study is introduced.

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)0.001
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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.022
GPT teacher head0.242
Teacher spread0.221 · 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

Citations11
Published2007
Admission routes1
Has abstractyes

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