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Record W1875996838 · doi:10.1109/iros.1994.407643

Robust hybrid impedance control of robot manipulators via a tracking control method

2002· article· en· W1875996838 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSoft Robotics and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsControl theory (sociology)Tracking errorTrajectoryImpedance controlTracking (education)Controller (irrigation)KinematicsBounded functionAccelerationRobotComputer scienceRobust controlConstraint (computer-aided design)Control engineeringControl (management)MathematicsEngineeringControl systemArtificial intelligencePhysics

Abstract

fetched live from OpenAlex

In this work, we address robust hybrid impedance control via a tracking control method. The objective of hybrid impedance control is converted into tracking a targeted trajectory. A globally asymptotically stable robust control law is proposed and applied to the tracking control of the targeted trajectory. The position and velocity tracking errors converge to zero under the proposed control law, and the force error is bounded. Furthermore, it is shown that the force error can be reduced by applying inner-loop acceleration feedback. The same controller can be used for control of both free and constraint motions of robot manipulator. As an illustration, an example is presented, and the simulation results are in accordance with the theoretical analysis.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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.

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: Methods · Consensus signal: none
Teacher disagreement score0.963
Threshold uncertainty score0.557

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 head0.029
GPT teacher head0.230
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

Quick stats

Citations12
Published2002
Admission routes1
Has abstractyes

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