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Record W2043870485 · doi:10.1115/detc2010-28257

Workspace Computation and Analysis of a Planar 2-DoF Translational Tensegrity Mechanism

2010· article· en· W2043870485 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicStructural Analysis and Optimization
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsWorkspaceTensegrityKinematicsMechanism (biology)PlanarCartesian coordinate systemComputer scienceInertiaAccelerationActuatorComputationGeometryTopology (electrical circuits)Control theory (sociology)RobotPhysicsEngineeringMathematicsClassical mechanicsArtificial intelligenceAlgorithm

Abstract

fetched live from OpenAlex

Tensegrity mechanisms are interesting candidates for high-acceleration robotic applications since their use of cables allows for a reduction in the weight and inertia of their mobile parts. In this work, a planar two-degree-of-freedom translational tensegrity mechanism that could be used for pick and place applications is introduced. The mechanism uses a strategic actuation scheme to generate the translational motion as well as to ensure that the cables remain taut at all times. Analytical solutions to the direct and inverse kinematic problems are developed and the mechanism’s workspace boundaries are computed in both the actuator and Cartesian spaces. The influence of the mechanism’s geometry on the size and shape of the Cartesian workspace are then studied. Based on workspace size only, it is found that the optimal mechanism geometry corresponds to a relatively large ratio between the length of the struts and the width of the base and end-effector.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.493
Threshold uncertainty score0.177

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 head0.005
GPT teacher head0.198
Teacher spread0.193 · 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

Quick stats

Citations3
Published2010
Admission routes1
Has abstractyes

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