Estimating the Angular Velocity From Body-Fixed Accelerometers
Bibliographic record
Abstract
This paper presents a novel way of determining the angular velocity of a rigid body from accelerometer measurements. This method finds application in crashworthiness and motion analysis in sports, for example, where impacts forbid the use of mechanical gyroscopes. Based on previous work, the time-integration (TI) and polynomial-roots (PR) estimates of the angular velocity are first computed. The TI and PR estimates are then linearly combined through a weighted sum whose weighting factor is chosen so as to minimize the `variance of the resulting estimate. The proposed method is illustrated in an experiment, where the twelve accelerometer array (OCTA) is moved manually. A comparison of the angular-velocity estimates obtained from the proposed method and those obtained from a magnetic displacement sensor shows that the resulting estimates are robust and do not suffer from the drift problems that hinder the TI method. Moreover, comparison with a previously reported method indicates that the method proposed here is less sensitive to measurement errors, especially at low angular velocities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".