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Record W2146671673 · doi:10.1109/robot.1997.620141

On the control of space free-flyers using multiple impedance control

2002· article· en· W2146671673 on OpenAlexafffund
S. Ali A. Moosavian, E. Papadopoulos

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSpace Satellite Systems and Control
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGRASPImpedance controlObject (grammar)Robot end effectorObstacleElectrical impedanceControl theory (sociology)Computer scienceBase (topology)Computer visionRobotArtificial intelligenceControl (management)EngineeringMathematicsElectrical engineeringLaw

Abstract

fetched live from OpenAlex

Multiple impedance control (MIC) is a new algorithm which enforces a designated impedance on both a manipulated object, and all cooperating manipulators. In this paper, the MIC is applied to a space robotic system in which robotic arms, mounted on a free-flying-base, manipulate an object. The general formulation of the MIC is extended to include the dynamic coupling between the arms and the base. It is shown that under the MIC law, all participating manipulators, the free-flyer base, and the manipulated object exhibit the same designated impedance behavior. This guarantees good tracking of system manipulators and the object, in performing a manipulation task. A system of two cooperating two-link manipulators is simulated, in which a remote centre compliance is attached to the second end-effector. The object is grabbed with a pivoted grasp condition, i.e. both the translational and rotational motions of the object have to be controlled by end-effector forces. As simulation results show, the response of the MIC algorithm is smooth, even in the occurrence of an impact due to collision with an obstacle.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.180
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 source (direct Gemma or distilled Codex), 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

Citations44
Published2002
Admission routes2
Has abstractyes

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