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Record W2145930998 · doi:10.1109/ical.2007.4338637

3D Kinematic Simulation for PA10-7C Robot Arm Based on VRML

2007· article· en· W2145930998 on OpenAlexaff
Wei‐Min Shen, Jason Gu, Yide Ma

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRobotic Mechanisms and Dynamics
Canadian institutionsDalhousie University
Fundersnot available
KeywordsInverse kinematicsVRMLKinematicsJacobian matrix and determinantRobot kinematicsRobot end effectorRobotCartesian coordinate systemRobotic armComputer scienceSimulationArtificial intelligenceMathematicsVirtual realityGeometryPhysicsApplied mathematicsClassical mechanicsMobile robot

Abstract

fetched live from OpenAlex

In this paper, a graphical, flexible, interactive, and systematic 3D simulation helps facilitate analyzing and previewing kinematics of PA10-7C robot arm in terms of forward kinematics, inverse kinematics, and the Denavit-Hartenberg convention. Modeling and control are of critical importance when the robot arm is used for practical applications. In the paper, the D-H model of PA10-7C robot arm is given first to describe the relationship between two consecutive frames of joints. Based on this D-H model, forward kinematics is calculated efficiently. To describe the relationship between joint angular velocities in the joint space and the end effector's velocities in Cartesian space, Jacobian matrix for PA10-7C robot arm is derived. By Jacobian matrix, inverse kinematics approach is obtained in the paper. VRML-based model of PA10-7C is built in the paper for the simulation. Finally, simulation results are discussed and the paper is concluded.

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: none
Teacher disagreement score0.575
Threshold uncertainty score0.369

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 head0.015
GPT teacher head0.249
Teacher spread0.234 · 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

Citations8
Published2007
Admission routes1
Has abstractyes

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