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Record W744679175

Position Control of Tendon-Driven Fingers

2011· article· en· W744679175 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

VenueNASA Technical Reports Server (NASA) · 2011
Typearticle
Languageen
FieldEngineering
TopicRobot Manipulation and Learning
Canadian institutionsMcGill University
Fundersnot available
KeywordsControl theory (sociology)Position (finance)Controller (irrigation)Tension (geology)Computer scienceTendonControl engineeringConstraint (computer-aided design)Scheme (mathematics)Work (physics)Control (management)Humanoid robotEngineeringRobotArtificial intelligenceMathematicsMechanical engineeringPhysics
DOInot available

Abstract

fetched live from OpenAlex

Conventionally, tendon-driven manipulators implement some force control scheme based on tension feedback. This feedback allows the system to ensure that the tendons are maintained taut with proper levels of tensioning at all times. Occasionally, whether it is due to the lack of tension feedback or the inability to implement sufficiently high stiffnesses, a position control scheme is needed. This work compares three position controllers for tendon-driven manipulators. A new controller is introduced that achieves the best overall performance with regards to speed, accuracy, and transient behavior. To compensate for the lack of tension feedback, the controller nominally maintains the internal tension on the tendons by implementing a two-tier architecture with a range-space constraint. These control laws are validated experimentally on the Robonaut-2 humanoid hand. I

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.606
Threshold uncertainty score0.695

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 head0.023
GPT teacher head0.221
Teacher spread0.197 · 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