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Record W2024670437 · doi:10.1109/icma.2010.5589215

Development of autonomous robot for space servicing

2010· article· en· W2024670437 on OpenAlexaff
Benoit P. Larouche, Zheng Zhu, S. A. Meguid

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTeleoperation and Haptic Systems
Canadian institutionsUniversity of New BrunswickUniversity of TorontoYork University
Fundersnot available
KeywordsComputer scienceController (irrigation)TrajectoryKalman filterMotion captureMotion planningRobotBearing (navigation)Control engineeringComputer visionControl theory (sociology)SimulationArtificial intelligenceMotion (physics)EngineeringControl (management)

Abstract

fetched live from OpenAlex

This paper focuses on the development of a test platform for the capture of non-cooperative targets by an autonomous robotic manipulator. The paper describes the platform and subsystems involved in the capture operation with an emphasis on the vision system and controller. The vision system employs a custom algorithm, detecting the target, determining the quality of the lock and predicting the motion through the use of a Kalman filter. Photogrammetry uses the information obtained to determine the translational and rotational vectors linking the camera to the target that is fed into the controller that determines the optimal path for capture and deceleration. The controller is developed based on a hybrid force-impedance control that follows a force trajectory based on the motion of the target and decelerates the target smoothly while monitoring potential vibrations in the system. Currently, the system is being validated through a combination of simulations and experiments that take place on an air-bearing table as well as a mobile pendulum system that simulates free fall environments.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.435
Threshold uncertainty score0.151

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 head0.013
GPT teacher head0.219
Teacher spread0.206 · 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 designBench or experimental
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

Citations3
Published2010
Admission routes1
Has abstractyes

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