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Record W3129180071 · doi:10.1115/1.4049975

Two Actuation Methods for a Complete Morphing System Composed of a VGTM and a Compliant Parallel Mechanism

2021· article· en· W3129180071 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 Mechanisms and Robotics · 2021
Typearticle
Languageen
FieldEngineering
TopicSoft Robotics and Applications
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsMorphingTrussMechanism (biology)KinematicsComputer scienceActuatorStewart platformControl engineeringSimulationEngineeringMechanical engineeringStructural engineeringArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract In this paper, a complete morphing system consisting of a variable geometry truss manipulator (VGTM) is presented that is fully covered by a flexible panel skin. Two approaches are studied for the morphing control. The first one is to have the VGTM act as a driving mechanism and the flexible panels as a passive system. In this case, the VGTM is composed of active members and passive lockable members. It is shown that the morphing system can reach the desired shapes through intermediate steps. The second method is to have the flexible panels act as drivers and the VGTM as a passive supporting structure. In this case, the VGTM is only composed of passive lockable members. The morphing system can also achieve the desired poses through several steps. The control strategies of the two methods are discussed along with kinematic analysis, a comparison study is conducted to show their pros and cons, two prototypes are fabricated, and experiments are carried out to verify the feasibility of two actuation methods.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.627
Threshold uncertainty score0.458

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 head0.037
GPT teacher head0.302
Teacher spread0.265 · 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