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Record W3040977249 · doi:10.1108/ir-05-2020-0109

Automatic robotic recharging systems – development and challenges

2020· article· en· W3040977249 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

VenueIndustrial Robot the international journal of robotics research and application · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced Manufacturing and Logistics Optimization
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsRobotService (business)Risk analysis (engineering)Computer scienceEngineering managementRoboticsWork (physics)Systems engineeringOriginalityField (mathematics)EngineeringArtificial intelligenceBusinessMarketing

Abstract

fetched live from OpenAlex

Purpose Since the market penetrations of service robots are only successful to a limited types of services, the purpose of the paper is to look into the reasons why the market penetrations are lagged from both technical and nontechnical perspectives. Automatic robotic recharging services, especially robotic refueling systems, are used as the case study for the investigation. Design/methodology/approach This paper surveyed the relevant technologies and products and conducted the feasibility study and risk management for new development of automated robotic refueling systems. This paper developed a cost model for the evaluation of robotic refueling systems. Findings There are no major technical barriers that exist for the development of robotic refueling systems, but two main risks of developing new robotic refueling systems are interference of existing patents and the extreme effort to further reduce the development cost of automated refueling systems. The recommendations have been made to new developers of service robots. Research limitations/implications The suggestions are made for further development on service robots, in general; however, this paper does not cover the physical development of service robots. Practical implications This study was actually conducted for a client company who has a strong interest in developing new products for automatic robotic refueling systems. The reported work has great significance for new comers in this area to understand the state of the art, technological challenges and some potential risks in the field. Originality/value To the best of authors’ knowledge, it will be the first academic paper to summarize the research and development effort on automatic recharging business. The targeted field is very typical in promoting robots in services. Even robotic refueling was proposed at very early stage of robotic application, the market penetration of refueling robots the market penetration is very limited, not because the technology readiness but some other factors. This work has its significance to identify technical and nontechnical challenges to promote robots in services.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.976
Threshold uncertainty score0.274

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.206
GPT teacher head0.324
Teacher spread0.118 · 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