MétaCan
Menu
Back to cohort
Record W1990459280 · doi:10.1115/detc2002/mech-34310

On the Development of Reactionless Spatial 3-DOF Parallel-Piped Mechanisms

2002· article· en· W1990459280 on OpenAlexafffund
Clément Gosselin, Yangnian Wu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRobotic Mechanisms and Dynamics
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsParallelepipedKinematicsMechanism (biology)TrajectoryComputer sciencePoint (geometry)InverseMaterial handlingSoftwareMotion (physics)Control theory (sociology)MathematicsGeometryClassical mechanicsPhysicsEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

In this paper, the design and dynamic balancing of a novel 3-DOF parallel mechanism referred to as parallelepiped mechanism are addressed. Two types of actuation schemes of the mechanism are considered. The balancing equations are derived by imposing that the center of mass of the mechanism is fixed and that the total angular momentum is constant with respect to a fixed point. Optimization is performed to determine the counter-weights and counter-rotations based on the balancing conditions. The dynamic simulation software ADAMS is used to simulate the motion of the 3-DOF parallelepiped mechanisms and to verify that the mechanisms are reactionless at all times and for any trajectory. A numerical example of a reactionless 3-DOF parallelepiped mechanism is given. It is shown that 3-DOF parallelepiped mechanisms can be completely balanced and used to synthesize 6-DOF reactionless manipulators. Additionally, the inverse and direct kinematic problems of the 3-DOF parallelepiped mechanisms as well as simulation tools for demonstrating the characteristics of the mechanisms are also introduced in this paper.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.778
Threshold uncertainty score1.000

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)0.0010.000

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 head0.021
GPT teacher head0.188
Teacher spread0.166 · 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.

Study designSimulation or modeling
Domainnot available
GenreMethods

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

Citations5
Published2002
Admission routes2
Has abstractyes

Explore more

Same topicRobotic Mechanisms and DynamicsFrench-language works237,207