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Record W7037001992

Design and development of an autonomous scaled electric combat vehicle

2019· dissertation· en· W7037001992 on OpenAlexaff

Bibliographic record

Venuee-scholar@UOIT (University of Ontario Institute of Technology) · 2019
Typedissertation
Languageen
FieldMedicine
TopicBerberine and alkaloids research
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsNucleofectionTSG101Gestational periodHyporeflexiaDiafiltrationFusible alloyArticular cartilage damageProteogenomics
DOInot available

Abstract

fetched live from OpenAlex

Current literature pertaining to multi-steerable mobile robots and the progression of military vehicles in the past few decades suggest a lack of effort in pursuing advanced technologies in this joint area. As a result, a novel scaled robotic platform that features independent wheel actuation and autonomous navigation capabilities is developed in this work to represent a potential future design of combat vehicles. The following thesis discusses the details of the mechanical systems in addition to the embedded electronics and software architecture. From there, previously developed mapping and path planning algorithms in addition to a developed localization algorithm are implemented to achieve autonomous navigation. Furthermore, a vision-based close quarter pose correction algorithm is designed and developed to improve upon the limitations imposed by current navigation methodologies. The result of this work is a proposed prototype capable of navigation and precise positioning.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.733
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.019
GPT teacher head0.246
Teacher spread0.226 · 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.

Study designOther design
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

Citations0
Published2019
Admission routes1
Has abstractyes

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