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Record W2107882824 · doi:10.1109/ccece.1996.548203

On trajectory control of multi-link robots with flexible links and joints

2002· article· en· W2107882824 on OpenAlexaff
Mehrdad Farid, Stanisław Łukasiewicz

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicDynamics and Control of Mechanical Systems
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsControl theory (sociology)Inverse dynamicsTrajectoryTorqueLink (geometry)RobotKinematicsInverse kinematicsComputer sciencePoint (geometry)Robot kinematicsMotion controlInverseControl engineeringControl (management)EngineeringMathematicsArtificial intelligenceMobile robotPhysicsClassical mechanics

Abstract

fetched live from OpenAlex

A technique based on numerical optimization is presented in this paper for solving the inverse dynamics and kinematics of multi-link robot arms with flexible links and joints. This technique finds the joint torques required to move the end point of flexible manipulators through specified trajectories while avoiding tip oscillations. Since the point for which the prescribed motion is specified and the application points of control torques are connected by elastic bodies, the inverse dynamics of flexible manipulators is non-causal. The proposed algorithm takes into account the non-causality of such systems by considering pre-actuation and post-actuation in the solution procedure.

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 score0.728
Threshold uncertainty score0.312

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 head0.013
GPT teacher head0.189
Teacher spread0.176 · 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

Citations4
Published2002
Admission routes1
Has abstractyes

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