Extra Large Aperture FPCB Mirror Based Scanning LiDAR
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Bibliographic record
Abstract
This article presents an extra-large (25 × 50 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ) flexible printed circuit board (FPCB) mirror to cover both the emitting and receiving lenses of a single-point LiDAR to form a biaxial scanning LiDAR with a compact structure and long measurement distance and low cost. The FPCB mirror is fabricated using the low cost and commercially available FPCB fabrication process. In addition, a widely available single–point LiDAR is used as the measurement unit. This article's novelty lies in the following two points: 1) integrating a large aperture scanning mirror and a single-point LiDAR (low cost and widely available) to construct a biaxial scanning LiDAR; 2) proposed a large aperture FPCB mirror using long existing FPCB process such as to achieve low cost. The scanning LiDAR is designed for applications in factory for robots and automated guided vehicles; navigation. The FPCB mirror consists of a mirror plate, two permanent magnets, and a FPCB structure, which includes two torsion beams, a middle seat, and a Flame retardant 4 (FR4) stiffener frame. Four-layer copper coils are embedded in the FPCB structure, which is fabricated using the low cost commercially available FPCB fabrication process. The mirror plate is diced from a thin silicon mirror plate with gold coating and then attached on top of the middle seat of the FPCB structure. With such large aperture FPCB scanning mirror, and a long measurement distance single-point LiDAR, a compact biaxial scanning LiDAR is constructed. The scanning LiDAR based on the FPCB mirror is constructed and tested. Achieved performances are: the field of view of 60°, measurement distance of 50 m, refresh rate of 20 Hz, 500 points for each scanning frame.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it