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Record W2036478283 · doi:10.1177/02783640122068227

Design of a Hollow Hexaform Torque Sensor for Robot Joints

2001· article· en· W2036478283 on OpenAlexaff
Farhad Aghili, M. Buehler, John M. Hollerbach

Bibliographic record

VenueThe International Journal of Robotics Research · 2001
Typearticle
Languageen
FieldEngineering
TopicRobot Manipulation and Learning
Canadian institutionsMcGill UniversityCanadian Space Agency
Fundersnot available
KeywordsTorqueSensitivity (control systems)StiffnessDamping torqueRobotWork (physics)EngineeringFinite element methodComputer scienceControl theory (sociology)Control engineeringDirect torque controlMechanical engineeringArtificial intelligenceElectronic engineeringStructural engineeringPhysicsElectrical engineeringControl (management)

Abstract

fetched live from OpenAlex

This work describes the design of a new one-axis torque sensor. It achieves the conflicting requirements of high stiffness for all six force and torque components, high sensitivity for the one driving torque of interest, and yet very low sensitivity for the other five force/torque components. These properties, combined with its donut shape and small size, make this sensor an ideal choice for direct-drive robotic applications. Experimental data validate the basic design ideas underlying the sensor’s geometry, the finite element model used in its optimization, and the advertised performance.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.194
GPT teacher head0.388
Teacher spread0.193 · 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

Citations65
Published2001
Admission routes1
Has abstractyes

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