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Record W1444095272

Integration and Assessment of Multiple Mobile Manipulators in a Real-World Industrial Production Facility

2014· article· en· W1444095272 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

VenueVBN Forskningsportal (Aalborg Universitet) · 2014
Typearticle
Languageen
FieldComputer Science
TopicRobotic Path Planning Algorithms
Canadian institutionsConvergent Manufacturing Technologies (Canada)
Fundersnot available
KeywordsProduction (economics)Computer scienceManufacturing engineeringSystems engineeringEngineeringEconomics
DOInot available

Abstract

fetched live from OpenAlex

This paper presents a large-scale research experiment carried out within the TAPAS project, where multiple mobile manipulators were integrated and assessed in an industrial context. We consider an industrial scenario in which mobile manipulators naturally extend automation of logistic tasks towards assistive ones. In the experiment, we included tasks such as preparatory and post-processing work, e.g. pre-assembly or machine tending with inherent quality control. In the experiment, we deployed the two heterogeneous mobile manipulators Little Helper and omniRob in a production scenario at Grundfos A/S, a manufacturer of water circulation pumps, in Denmark. The experiment showed that mobile manipulation is at a level of technology readiness that will allow industrial application in the near future. Despite challenges indicated later in the paper, the research efforts presented do show that research is on the right track on transferring mobile manipulation from research to industry.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.382
Threshold uncertainty score0.701

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.032
GPT teacher head0.266
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