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Record W2086684929 · doi:10.1109/robio.2013.6739854

Dynamic analysis and control system of spherical robot for polar region scientific research

2013· article· en· W2086684929 on OpenAlexaff
Shaorong Xie, Jiqing Chen, Jun Luo, Hengyu Li, Junfeng Yao, Jason Gu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicControl and Dynamics of Mobile Robots
Canadian institutionsDalhousie University
Fundersnot available
KeywordsRobotPolarComputer scienceControl (management)Control systemControl engineeringControl theory (sociology)Artificial intelligenceEngineeringPhysicsElectrical engineeringAstronomy

Abstract

fetched live from OpenAlex

To figure out the limitation of enough power resource or energy supplied in Antarctic expedition, this paper presented a large-size spherical robot which can drive by internal power and wind. It consists of a 2-DOF pendulum inside the shell, rotating with transverse and longitudinal axis. Due to the non-holonomic restraint of motion, for smooth and steady control, the spherical robot is designed to finish its movement by turning and linear motion independently, and simpler through decouple method. Base on this, a dynamic model of spherical robot is developed using Lagrange, and analyzed the dynamic characteristic. Further, the hardware implementations and software system are introduced. The test result showed that rolling angular velocity and pendulum angle approach to stability with smart steering, fast rolling, and accomplish common detection mission.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.012
GPT teacher head0.247
Teacher spread0.235 · 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 source (direct Gemma or distilled Codex), 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

Citations10
Published2013
Admission routes1
Has abstractyes

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