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Record W2074926812 · doi:10.1109/isie.2006.296112

New XY-Theta Positioning Table with Partially Decoupled Parallel Kinematics

2006· article· en· W2074926812 on OpenAlexaff
Alexander Yu, Ilian A. Bonev, Paul Zsombor-Murray

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRobotic Mechanisms and Dynamics
Canadian institutionsÉcole de Technologie SupérieureMcGill University
Fundersnot available
KeywordsWorkspaceKinematicsRobotParallel manipulatorComputer scienceActuatorTable (database)Robot kinematicsControl theory (sociology)Control engineeringMobile robotControl (management)Artificial intelligenceEngineering

Abstract

fetched live from OpenAlex

Parallel robots provide an efficient solution in a world demanding better positioning accuracy. These robots are preferred over their serial counterparts because each leg helps support the platform, thus reducing the need to add means for extra support. The problem with parallel robots though is that most are coupled and difficult to control. In this paper, new parallel robot architecture has been proposed that can deliver accurate movements in addition to being partially decoupled and fast. This is a significant technological advantage over current designs because a decoupled robot is simpler to control as each actuator is independent. Furthermore, its displacement resolution is less variable throughout the workspace. To achieve the decoupled state, this parallel robot took the novel approach of having mixed legs. By comparing this robot to existing commercial devices through kinematic, singularity, workspace, velocity and dexterity analysis, this paper would like to show that this new design should be looked into further to create a precision positioning table that is parallel, decoupled, and highly accurate

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.078
Threshold uncertainty score0.474

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 head0.004
GPT teacher head0.166
Teacher spread0.163 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations17
Published2006
Admission routes1
Has abstractyes

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