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Record W2751172584 · doi:10.11159/cdsr17.124

Motion Control of a Wheeled Millirobot

2017· article· en· W2751172584 on OpenAlexafffundabout
Rachel Drisdelle, Zendai Kashino, Laura Pineros, Justin Y. Kim, Goldie Nejat, B. Benhabib

Bibliographic record

VenueProceedings of the International Conference of Control, Dynamic systems, and Robotics · 2017
Typearticle
Languageen
FieldEngineering
TopicControl and Dynamics of Mobile Robots
Canadian institutionsUniversity of TorontoUniversity of New Brunswick
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsMotion controlComputer scienceMotion (physics)Control (management)Computer visionArtificial intelligenceRobot

Abstract

fetched live from OpenAlex

This paper presents a new closed-loop control system for a novel wheeled millirobot, mROBerTO, developed at the University of Toronto.The proposed system was verified via vision-based robot-pose tracking, a centralized computer for directing movement, and a firmware PID controller.Further modification to the original robot structure, via the addition of stabilizing arms, was made to improve tracking performance.Numerous motion-control experiments were performed to evaluate the performance and robustness of the controller on the millirobot.The system presented is simple, requires little knowledge of robot's motion characteristics, and consumes limited processing capabilities.Furthermore, experimental results show that the system can provide accurate motion control for various trajectories despite the limitations that result from the small footprint of mROBerTO, 16×16×32 mm 3 .

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.007

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.220
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 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

Citations4
Published2017
Admission routes3
Has abstractyes

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Same venueProceedings of the International Conference of Control, Dynamic systems, and RoboticsSame topicControl and Dynamics of Mobile RobotsFrench-language works237,207