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Record W2063690171 · doi:10.1109/icmech.2006.252592

An Environment for Programming and Control of Multi-Robot Manipulators

2006· article· en· W2063690171 on OpenAlexaffabout
Mehrdad Moallem, R. Khoshbin

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRobot Manipulation and Learning
Canadian institutionsWestern University
Fundersnot available
KeywordsRobotComputer scienceRoboticsScheduling (production processes)Modular designSoftwareRobot controlTask (project management)Software architectureEmbedded systemCollision avoidanceSupervisory controlMobile robotReal-time computingArtificial intelligenceEngineeringControl (management)Operating systemSystems engineeringCollision

Abstract

fetched live from OpenAlex

This paper discusses the development of an open architecture multi-robot system. The environment consists of five serial-link robot manipulators in the ECE robotics laboratory at the University of Western Ontario, Canada. The robots are operated under their original controllers which are connected together through a network of supervisory computers. A preemptive multi-tasking real time operating system (RTOS) running on these computers is used to perform supervisory and cooperative tasks involving multiple robots. The software environment allows for controlling the motion of one or more robots and their interaction with other devices. Development of modular components is discussed in this paper along with typical laboratory procedures with a link to a short video demonstration for a multi-robot object handling task. The environment is used to train undergraduate and graduate students on how to develop software for various robotic applications, including scheduling techniques, cooperative manipulation, collision avoidance, and emerging robotic applications

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: Empirical · Consensus signal: none
Teacher disagreement score0.903
Threshold uncertainty score0.252

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 head0.222
Teacher spread0.207 · 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
GenreEmpirical

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

Citations2
Published2006
Admission routes2
Has abstractyes

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