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Record W1841194845 · doi:10.1109/ccece.1996.548199

Stability of robot force control applied to unilateral constraints

2002· article· en· W1841194845 on OpenAlexaff
P.B. Goldsanith

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRobot Manipulation and Learning
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsConstraint (computer-aided design)Control theory (sociology)RobotNonlinear systemLimit cycleStability (learning theory)Contact forceLimit (mathematics)MathematicsComputer scienceControl (management)PhysicsArtificial intelligenceClassical mechanicsMathematical analysis

Abstract

fetched live from OpenAlex

Experiments on single degree of freedom (1-DOF) robots have shown that force feedback sometimes produces an undesirable chattering behaviour, where the robot repeatedly makes and breaks contact with the constraint surface. This behaviour is an example of a limit cycle, and is likely caused by the nonlinearity in the system dynamics introduced by the unilateral (i.e. one-sided) constraint. Yet most published stability analyses of force-controlled robots assume that the constraint is bilateral, meaning the robot never loses contact with the constraint. In this paper, we analyse the stability of a 1-DOF force-controlled robot in contact with a rigid unilateral constraint, with the force sensor modelled as a stiff spring. It is proved that the nonlinear system is globally, asymptotically stable and achieves zero steady-state force error.

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 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 score0.879
Threshold uncertainty score0.997

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)0.0040.000

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 head0.024
GPT teacher head0.202
Teacher spread0.178 · 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.

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

Citations4
Published2002
Admission routes1
Has abstractyes

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