Six Degree-of-Freedom Positioner for Optical Components
Bibliographic record
Abstract
The Six Degree-of-Freedom (6DOF) positioner was developed to position the four off-axis conic mirrors in Altair (Gemini** North's facility adaptive optics system). This positioner takes a unique approach to 6DOF positioning by combining two 3DOF parallel mechanisms in series to create a hybrid mechanism. The mechanism design provides a number of benefits including small size, simple adjustment, position locking, relatively simple kinematics and repeatable removal and replacement of optical components. The 6DOF positioner is capable of positioning optics at the micron level in translation and at the arcsecond level in rotation. It also maintains the position of the optics to a few microns with changing gravity vector. The position of an attached optical component can be adjusted using a computer program to provide precision adjustment about an arbitrary coordinate system. However, the arrangement of the adjustments are such that any desired motion can be made with a single actuator or with a sensible combination of actuators. This is unlike other 6DOF positioning solutions like a Stewart Platform in which all 6DOF are completely coupled making it impossible to move the platform in any desired direction without moving all six actuators. This paper will present the design of the positioner, a kinematic analysis of the mechanism and a discussion about the effectiveness of the positioner in the optical alignment of Altair.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.005 |
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".