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Record W2166002162 · doi:10.5589/q13-003

Investigation of impedance controller for autonomous on-orbit servicing robot

2013· article· en· W2166002162 on OpenAlexaffvenue
Benoit P. Larouche

Bibliographic record

VenueCanadian aeronautics and space journal · 2013
Typearticle
Languageen
FieldEngineering
TopicSpace Satellite Systems and Control
Canadian institutionsYork University
Fundersnot available
KeywordsControl theory (sociology)Control engineeringImpedance controlEngineeringController (irrigation)TorqueEncoderRobotOrbit (dynamics)Electrical impedanceControl (management)Computer scienceArtificial intelligenceAerospace engineeringPhysicsElectrical engineering

Abstract

fetched live from OpenAlex

The premise of this study is to demonstrate a simulation environment and basis that is used to evaluate the control methodologies employed to govern the behaviour of robotic manipulators (RM) in on-orbit autonomous capture. The capture itself is effected on non-cooperative targets in a zero gravity simulated environment. The RM employs a vision system, force sensors, and encoders to sense its environment. The control is effected through position and torque inputs to three stepper motors and three servo motors. The control strategy tested is a modified hybrid force/neural network impedance controller. This paper will demonstrate that impedance control can reliably control a robotic manipulator in an unknown environment.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.654
Threshold uncertainty score0.938

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 head0.009
GPT teacher head0.178
Teacher spread0.168 · 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

Citations9
Published2013
Admission routes2
Has abstractyes

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