MétaCan
Menu
Back to cohort
Record W2006830626 · doi:10.1177/0278364908099464

Scaling Inertia Properties of a Manipulator Payload for 0- <i>g</i> Emulation of Spacecraft

2009· article· en· W2006830626 on OpenAlexaff
Farhad Aghili, Mehrzad Namvar

Bibliographic record

VenueThe International Journal of Robotics Research · 2009
Typearticle
Languageen
FieldEngineering
TopicSpace Satellite Systems and Control
Canadian institutionsCanadian Space Agency
Fundersnot available
KeywordsEmulationPayload (computing)SpacecraftInertiaScalingAerospace engineeringManipulator (device)Computer scienceControl theory (sociology)PhysicsEngineeringClassical mechanicsRobotMathematicsArtificial intelligenceGeometryPsychologyControl (management)

Abstract

fetched live from OpenAlex

This paper presents a method to control a manipulator system grasping a rigid-body payload so that the motion of the combined system as a consequence of external applied forces is the same as any other free-floating rigid-body (with different inertial properties). This allows 0-g emulation of a scaled spacecraft prototype under the test in a 1-g laboratory environment. The controller consisting of motion feedback and force/moment feedback adjusts the motion of the test spacecraft so as to match that of the flight spacecraft, even if the latter has flexible appendages (such as solar panels) and the former is rigid. The stability of the overall system is analytically investigated, and the results show that the system remains stable provided that the inertial properties of two spacecraft are different and that an upperbound on the norm of the inertia ratio of the payload to the manipulator is respected. Important practical issues such as calibration and sensitivity analysis to sensor noise and quantization are also presented. Finally, experimental results obtained from a robotic setup for spacecraft emulation with a milli-gravity accuracy are presented.

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)0.001
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 score0.157
Threshold uncertainty score0.175

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.084
GPT teacher head0.334
Teacher spread0.249 · 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

Citations24
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueThe International Journal of Robotics ResearchSame topicSpace Satellite Systems and ControlFrench-language works237,207