A Reparametrization of the Rotation Matrix in Rigid-Body Dynamics
Bibliographic record
Abstract
The parametrization of a rigid-body rotation is a classical subject in rigid-body dynamics. Euler angles, the rotation matrix and quaternions are the most common representations. However, Euler angles are known to be prone to singularities, besides not being frame-invariant. The full 3 × 3 rotation matrix conveys all the motion information, but poses the problem of an excessive number of parameters, nine, to represent a transformation that entails only three independent parameters. Quaternions are singularity-free, and thus, ideal to study rigid-body kinematics. However, quaternions, comprising four components, are subject to one scalar constraint, which has to be included in the mathematical model of rigid-body dynamics. The outcome is that the use of quaternions imposes one algebraic constraint, even in the case of mechanically unconstrained systems. An alternative parametrization is proposed here, that (a) comprises only three independent parameters; (b) is fairly robust to representation singularities; and (c) satisfies the quaternion scalar constraint intrinsically. To illustrate the concept, a simple, yet nontrivial case study is included. This is a mechanical system composed of a rigid, toroidal wheel rolling without slipping or skidding on a horizontal surface. The simulation algorithm based on the proposed parametrization and fundamentally on quaternions, together with the invariant relations between the quaternion rate of change and the angular velocity, is capable of reproducing the falling of the wheel under deterministic initial conditions and a random disturbance acting on the tilting axis. Finally, a comparative study is included, on the numerical conditioning of the parametrization proposed here and that based on Euler angles. Ours shows as broader well-conditional region than Euler angles offer. Moreover, the two parametrizations exhibit an outstanding complementarity: where the conditioning of one degenerates, the other comes to rescue.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".