MétaCan
Menu
Back to cohort
Record W1979072890 · doi:10.1115/detc2013-12496

Design of Isotropic Accelerometer Strapdowns for Rigid-Body Pose-and-Twist Estimation

2013· article· en· W1979072890 on OpenAlexaff
Ting Zou, Jorge Angeles

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicInertial Sensor and Navigation
Canadian institutionsMcGill University
Fundersnot available
KeywordsCentripetal forceAccelerometerAccelerationRigid bodyIsotropyTwistPoseControl theory (sociology)KinematicsPoint (geometry)Computer scienceCoupling (piping)PhysicsMathematicsClassical mechanicsComputer visionEngineeringArtificial intelligenceGeometryOpticsMechanical engineering

Abstract

fetched live from OpenAlex

Coupling of tangential and centripetal acceleration components occurs in the estimation of rigid-body pose and twist with current accelerometer strapdowns. To address this shortcoming and its pernicious effects, a novel design of biaxial accelerometer strapdown is proposed. By virtue of its inherent isotropy, point tangential acceleration is decoupled from its centripetal counterpart, thereby realizing a straightforward and accurate acceleration estimation. The algorithm associated with the strapdown is validated by means of a numerical example, which shows the precision of the strapdown in estimating rigid-body pose and twist.

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)0.001
metaresearch head score (Gemma)0.002
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: Methods · Consensus signal: Methods
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.015
GPT teacher head0.221
Teacher spread0.206 · 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
GenreMethods

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

Citations2
Published2013
Admission routes1
Has abstractyes

Explore more

Same topicInertial Sensor and NavigationFrench-language works237,207