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Record W2032268716 · doi:10.2514/2.4785

Experimental Evaluation of Flexible Manipulator Trajectory Optimization

2001· article· en· W2032268716 on OpenAlexafffund
Burke Pond, Inna Sharf

Bibliographic record

VenueJournal of Guidance Control and Dynamics · 2001
Typearticle
Languageen
FieldEngineering
TopicDynamics and Control of Mechanical Systems
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTrajectoryTrajectory optimizationControl theory (sociology)VibrationComputer sciencePoint (geometry)Interval (graph theory)Joint (building)Optimization problemEnergy (signal processing)Mathematical optimizationMathematicsAlgorithmEngineeringPhysicsStructural engineeringArtificial intelligence

Abstract

fetched live from OpenAlex

Experimental results showing the effectiveness of trajectory optimization for reducing vibration excitation in point-to-pointmaneuvers of  exible manipulators are presented. Joint trajectories are found as the solution to a functional (or global) optimization problem. To reduce vibration, the functional is chosen to be the strain energy of the manipulator integrated over the time interval of the motion. A numerical example is presented to help verify the algorithm. A laboratory-based  exible-link manipulator is then described, and a model of its dynamics is obtained by combining analysis with experimental parameter identiŽ cation. Through the use of the model, the optimal trajectory is generated and compared, both in simulation and experimentally, to a polynomial trajectory and the globallyoptimalstraight-linetrajectory. The experiments agree with the simulationin conŽ rming that joint trajectory optimization can signiŽ cantly reduce the total strain energy incurred during point-to-pointmotions.

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)0.001
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 score0.511
Threshold uncertainty score0.369

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.241
Teacher spread0.228 · 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

Citations11
Published2001
Admission routes2
Has abstractyes

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