Crosstalk-free large aperture electromagnetic 2D micromirror for LiDAR application
Bibliographic record
Abstract
Abstract This paper presents a novel design of a 2D electromagnetic micromirror without crosstalk. The proposed micromirror uses a flexible printed circuit board (FPCB) and four layers of coils embedded in the polyimide layers. The insulated layers of the coil allow for independent actuation of the mirror plate to rotate about two orthogonal axes. The diamond shaped micromirror uses a hyperbola-shaped magnetic field on the coils under the mirror plate and a 45-degrees magnetic field on the coils embedded in the FPCB frame to eliminate the mechanical crosstalk. Finite element analysis was used to predict the novel 2D micromirror’s behavior. The novel 2D micromirror prototype is used in scanning LiDAR, The results indicate that the crosstalk-free pattern yielded significantly clearer results, particularly for detecting object boundaries and reducing barrel distortion. The experimental test has verified the novel crosstalk-free 2D micromirror working principle and showed good scanning quality: no crosstalk and an improvement in the horizontal field of view up to 19% But with the cost of reducing the vertical field of view by up to 12%. The novel 2D micromirror prototype has a large aperture of 19 × 19 mm2, which is very suitable for coaxial scanning LiDAR.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".