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Record W4246276126 · doi:10.1002/9780470050118.ecse204

Robot Kinematics

2008· other· en· W4246276126 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

VenueWiley Encyclopedia of Computer Science and Engineering · 2008
Typeother
Languageen
FieldEngineering
TopicRobotic Mechanisms and Dynamics
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsKinematicsInverse kinematicsJacobian matrix and determinantTransformation matrixEuler anglesTranslation (biology)Robot kinematicsComputer scienceDegrees of freedom (physics and chemistry)Parallel manipulatorControl theory (sociology)Transformation (genetics)Rotation (mathematics)Forward kinematicsRobotMathematicsArtificial intelligenceGeometryClassical mechanicsPhysicsApplied mathematics

Abstract

fetched live from OpenAlex

Abstract In this article, kinematics of robot manipulators is presented with a systematic and general approach—Denavit‐Hartenberg convention. The basic mathematical concepts are explained in detail, including translational transformation, rotational transformation, homogeneous transformation, Euler angle, direct kinematics and inverse kinematics, and so on. The relation between joint velocities and end‐effector linear and angular velocities is described by the Jacobian matrix. As an example, a parallel manipulator with three degrees of freedom (DOFs) is presented. This 3DOF‐parallel manipulator can be used for machine tools, and it includes two rotations and one translation along the z axis. Both direct and inverse kinematic problems are conducted based on the theory described in the beginning of the article. The case study will allow readers to better understand the knowledge of robot kinematics.

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 categoriesMeta-epidemiology (narrow)
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 score0.090
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)0.0000.000

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 head0.177
Teacher spread0.172 · 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