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Record W2024402035 · doi:10.1115/1.4004028

A Compact 3 Degree of Freedom Spherical Joint

2011· article· en· W2024402035 on OpenAlexaff
Mark L. Guckert, Michael D. Naish

Bibliographic record

VenueJournal of Mechanisms and Robotics · 2011
Typearticle
Languageen
FieldEngineering
TopicRobotic Mechanisms and Dynamics
Canadian institutionsLawson Health Research InstituteWestern University
Fundersnot available
KeywordsKinematicsJoint (building)Degrees of freedom (physics and chemistry)Control theory (sociology)MiniaturizationGravitational singularityComputer scienceRoboticsMechanical systemWork (physics)Control engineeringMechanical engineeringRobotMathematicsEngineeringArtificial intelligenceClassical mechanicsPhysicsControl (management)Structural engineeringMathematical analysis

Abstract

fetched live from OpenAlex

Spherical joints have evolved into a critical component of many robotic systems, often used to provide dexterity at the wrist of a manipulator. In this work, a novel 3 degree of freedom spherical joint is proposed, actuated by tendons that run along the surface of the sphere. The joint is mechanically simple and avoids mechanical singularities. The kinematics and mechanics of the joint are modeled and used to develop both open- and closed-loop control systems. Simulated and experimental assessment of the joint performance demonstrates that it can be successfully controlled in 3 degrees of freedom. It is expected that the joint will be a useful option in the development of emerging robotic applications, particularly those requiring miniaturization.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

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 studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.044
GPT teacher head0.210
Teacher spread0.166 · 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

Citations9
Published2011
Admission routes1
Has abstractyes

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