MétaCan
Menu
Back to cohort
Record W2145202816 · doi:10.1109/robot.2009.5152416

Concurrent synthesis of robot manipulators using Hardware-in-the-loop Simulation

2009· article· en· W2145202816 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicModular Robots and Swarm Intelligence
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMechatronicsModular designControl engineeringKinematicsComputer scienceScope (computer science)Robot manipulatorRobotConcurrent engineeringEngineeringArtificial intelligenceProgramming language

Abstract

fetched live from OpenAlex

This paper discusses a practical approach to the concurrent synthesis of robot manipulators, which is based on the alternative design methodology of linguistic mechatronics (LM) as well as the utilization of a modular robotic hardware-in-the-loop simulation (RHILS) platform. The RHILS platform involves physical joint modules and the control unit to reduce modeling complexities while taking into account various physical phenomena. The LM methodology simplifies the multi-objective constrained optimization problem into a single-objective unconstrained formulation and also brings subjective notions of design into the scope. The new approach is applied to redesigning kinematic, dynamic and control parameters of an industrial manipulator.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.571
Threshold uncertainty score0.288

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 head0.049
GPT teacher head0.288
Teacher spread0.239 · 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

Quick stats

Citations8
Published2009
Admission routes1
Has abstractyes

Explore more

Same topicModular Robots and Swarm IntelligenceFrench-language works237,207