MétaCan
Menu
Back to cohort
Record W3186524155 · doi:10.2514/1.a34881

Adaptive Control of a Tendon-Driven Manipulator for Capturing Non-Cooperative Space Targets

2021· article· en· W3186524155 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Spacecraft and Rockets · 2021
Typearticle
Languageen
FieldEngineering
TopicSpace Satellite Systems and Control
Canadian institutionsCarleton University
Fundersnot available
KeywordsControl theory (sociology)Controller (irrigation)TrajectoryTransmission (telecommunications)Mechanism (biology)Computer scienceNonlinear systemControl engineeringEngineeringSimulationControl (management)PhysicsArtificial intelligence

Abstract

fetched live from OpenAlex

Orbital debris in Earth orbit poses a threat to the future of spaceflight. To combat this issue, this paper proposes a novel robotic mechanism for non-cooperative capture and active servicing missions on non-cooperative targets; specifically, a tendon-driven manipulator is assumed for this work. The capture mechanism is a prototype symmetric two-link gripper driven by an open-ended cable-sheath transmission mechanism. Because the cable-sheath transmission mechanism is a nonlinear time-varying hysteretic system, two separate adaptive control strategies were compared against the uncontrolled and proportional-integral-derivative controlled performance of the closed-loop gripper. Specifically, an indirect control method and a direct controller were employed. Experimental results demonstrate that the adaptive controllers show better tracking performance of a joint trajectory over the proportional-integral-derivative controlled and uncontrolled cases, whereas the controller performs best under dynamic conditions, and the indirect controller performs best in steady state.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.471
Threshold uncertainty score0.670

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.007
GPT teacher head0.199
Teacher spread0.192 · 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