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Record W1893323080 · doi:10.1109/isic.1993.397729

Nonlinear dynamic feedback technique for motion control in holonomic robotic systems

2002· article· en· W1893323080 on OpenAlexaff
A. Kapitanovsky, A.A. Goldenberg, James K. Mills

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRobotic Mechanisms and Dynamics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHolonomicCartesian coordinate systemControl theory (sociology)Nonlinear systemTrajectoryComputer scienceMotion controlObstacle avoidanceMotion (physics)Convergence (economics)RobotMathematicsControl engineeringArtificial intelligenceMobile robotControl (management)Engineering

Abstract

fetched live from OpenAlex

A nonlinear dynamic feedback design technique for globally optimal motion control in a class of holonomic systems (e.g., robot manipulators and closed-link robotic mechanisms) is developed. The proposed technique provides asymptotically stable convergence to a desired equilibrium state defined as a (task) function of the Cartesian (e.g., end-effector) coordinates, as well as marginally stable tracking of a desired Cartesian trajectory. The problem of obstacle avoidance is addressed. It is shown that the proposed technique works for redundant systems, as well as for non-redundant ones. Applications of the proposed technique and numerical simulation results are presented.>

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.008

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.198
Teacher spread0.188 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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

Citations0
Published2002
Admission routes1
Has abstractyes

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