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Record W1697323122 · doi:10.1109/acc.1995.529275

On the effect of compliance in robotic contact task problem

2005· article· en· W1697323122 on OpenAlexafffund
Shahram Payandeh

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRobot Manipulation and Learning
Canadian institutionsSimon Fraser University
FundersNational Research Council Canada
KeywordsControl theory (sociology)Stability (learning theory)Controller (irrigation)Computer scienceTask (project management)RobotRobot manipulatorManipulator (device)Lyapunov stabilityClosed loopLyapunov functionCompliance (psychology)Control engineeringProperty (philosophy)Control (management)EngineeringArtificial intelligenceNonlinear systemPhysics

Abstract

fetched live from OpenAlex

Generally, in most dexterous manipulation tasks the manipulator undergoes a transition from free motion to contact configuration with its environment. An example can be the exploratory unconstrained motions of the force guided manipulator for establishing contact with an environment. This transition usually involves the impact stage. The impact usually results in an unstable performance of the closed-loop controller of the manipulator. One of the main remedies to achieve a stable closed-loop control of the manipulator is to introduce some compliance property into the closed-loop system. Based on the second method of Lyapunov and the theory of guaranteed stability of uncertain systems, this paper presents results on showing the effect of compliance in increasing the stability bounds of the manipulator during the impact phase. Experimental results are also presented to demonstrate the effect of compliance in the stable response of the manipulator during the impact phase.

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: Empirical
Teacher disagreement score0.255
Threshold uncertainty score0.240

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 head0.019
GPT teacher head0.239
Teacher spread0.220 · 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

Citations2
Published2005
Admission routes2
Has abstractyes

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