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Record W2322497546 · doi:10.1115/imece2012-89585

Dynamics and Motion Control of a 6-DOF Robot Manipulator

2012· article· en· W2322497546 on OpenAlexaff
Carlos Mondragon, Reza Fotouhi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicRobotic Path Planning Algorithms
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsWorkspaceMobile manipulatorKinematicsComputer sciencePath (computing)SMT placement equipmentRobotMotion planningRobotic armSimulationTrajectoryParallel manipulatorRobot kinematicsCollisionMotion controlObject (grammar)Motion (physics)Control engineeringMobile robotEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

This research work is to control motion of a manipulator attached to a mobile robot for pick-and-place operations; this is part of a bigger project in developing a robotic-assisted nursing to be used in medical settings. In this paper a strategy to accomplish pick-and-place operations, using a six degree-of-freedom robotic arm, is presented. Such operations are completed by creating a collision-free path to move an object from an initial to a final position. The collision-free path is planned by considering the entire workspace of the manipulator. The workspace is defined as the subtraction of the stationary objects and the robot volumes from all of the possible reachable points of the robotic arm. Once the path is planned, the kinematics of the manipulator is considered. Although this project can be applied into a wide range of applications, it is mainly intended to be used for medical robotic assistance. Simulation results for several different paths are presented. The simulation results were verified with experimental results, although not shown here.

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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.898
Threshold uncertainty score0.230

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 head0.235
Teacher spread0.219 · 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

Citations1
Published2012
Admission routes1
Has abstractyes

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