MétaCan
Menu
Back to cohort

A MODEL FOR OPTIMIZATION AND CONTROL OF SPATIAL COMPLIANT MANIPULATORS

2006· article· en· W2045366815 on OpenAlexvenueno aff
Stephen L. Canfield, James W. Beard

Bibliographic record

VenueInternational Journal of Robotics and Automation · 2006
Typearticle
Languageen
FieldEngineering
TopicPiezoelectric Actuators and Control
Canadian institutionsnot available
Fundersnot available
KeywordsKinematicsComputer scienceInverse kinematicsCompliant mechanismSensitivity (control systems)Control engineeringControl theory (sociology)Parallel manipulatorInverseRobotControl (management)Finite element methodEngineeringArtificial intelligenceMathematics

Abstract

fetched live from OpenAlex

This paper will present a kinetoelastic model appropriate for spatial compliant manipulators that will be used for size optimization and motion control of these devices. This model will be applicable to a class of compliant manipulators based on a parallel architecture that combines the characteristics of parallel manipulators with the low-cost, small-scale capabilities resulting from a compliant structure design. The model will address both the forward and inverse kinematic analysis of such devices, as well as form a design tool for dimensional synthesis in an optimal sense based on sensitivity to joint strain limits and manufacture, parameters that are critical in the performance of compliant manipulators. The model will then be applied to a specific compliant 3-degree-of-freedom manipulator topology to demonstrate its use in size optimization of the dimensional parameters of the selected compliant manipulator. The ability of the model to accurately solve the forward and inverse kinematics will also be evaluated through testing with the prototype. The authors provide a general discussion geared to the future implementation of this model in control of positioning compliant manipulators.

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 score0.948
Threshold uncertainty score0.192

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 head0.007
GPT teacher head0.208
Teacher spread0.200 · 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

Citations2
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Robotics and AutomationSame topicPiezoelectric Actuators and ControlFrench-language works237,207