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Record W2140812278 · doi:10.1109/plans.2004.1308980

Initial calibration of an inertial measurement unit using an optical position tracking system

2004· article· en· W2140812278 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Measurement and Metrology Techniques
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsInertial measurement unitAccelerometerCalibrationKinematicsPosition (finance)AccelerationComputer visionComputer scienceTracking (education)QuaternionInertial reference unitInertial frame of referenceOrientation (vector space)Units of measurementArtificial intelligenceGyroscopeInertial navigation systemControl theory (sociology)EngineeringMathematicsPhysicsAerospace engineering

Abstract

fetched live from OpenAlex

A reliable calibration procedure of a standard six degree-of-freedom inertial measurement unit (IMU) is presented. Mathematical models are derived for the three accelerometers and three rate gyros, taking into account the sensor axis misalignments, accelerometer offsets, electrical gains, and biases inherent in the manufacture of an IMU. The inertial sensors are calibrated using data from a 3D optical tracking system that measures the position coordinates of markers attached to the IMU. Inertial sensor signals and optical tracking data are obtained by manually moving the IMU. Using vector methods, the quaternion corresponding to the IMU platform orientation is obtained, along with its acceleration, velocity, and position. Given this kinematics information, the sensor models are used in a nonlinear least squares algorithm to solve for the unknown calibration parameters. The calibration procedure is verified through extensive experimentation.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.476
Threshold uncertainty score0.446

Codex and Gemma teacher scores by category

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 communication0.0000.001
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 head0.080
GPT teacher head0.295
Teacher spread0.215 · 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