MétaCan
Menu
Back to cohort
Record W2132058110 · doi:10.1109/robot.1991.131589

Robust hybrid impedance control of robot manipulators

2002· article· en· W2132058110 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
TopicRobot Manipulation and Learning
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsImpedance controlControl theory (sociology)Subspace topologyInertiaElectrical impedanceComputer scienceLinear subspaceAccelerationRobotController (irrigation)PID controllerTrajectoryControl engineeringEngineeringArtificial intelligenceMathematicsControl (management)Physics

Abstract

fetched live from OpenAlex

The objective of hybrid impedance control is defined, and a robust hybrid impedance control method is proposed. The task space is split into force-controlled and position-controlled subspaces based on the concept of hybrid control. Desired inertia and damping are introduced in the force control subspace to improve the dynamic behavior, and impedance control is used in the position-controlled subspace. In the proposed control scheme, the hybrid impedance control is equivalent to tracking a desired acceleration trajectory, which is generated in real-time. The computed torque technique and a PI control law are used to reduce the influence of model uncertainties. Experimental results obtained with a two-degree-of-freedom direct drive robot have shown the effectiveness of the proposed hybrid impedance control method.< <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 categoriesInsufficient payload (model declined to judge)
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 score0.936
Threshold uncertainty score0.999

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)0.0020.000

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 head0.036
GPT teacher head0.192
Teacher spread0.156 · 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

Citations108
Published2002
Admission routes1
Has abstractyes

Explore more

Same topicRobot Manipulation and LearningFrench-language works237,207