Zero-crossing edge detection for visual force measurement in assembly of MEMS devices
Bibliographic record
Abstract
In this paper, a new visual force sensor is proposed to measure the microforces acting upon the jaws of passive, compliant microgrippers, used to construct out-of-plane 3-D microstructures. The vision-based force measurement technique is reduced to determining the deflections of the microgripper jaws during the microassembly process. A computer vision system is used to measure the deflections in the gripper's jaws during the joining and grasping processes. A mathematical model of the microgripper system was developed where a relation between the force and the jaw displacement was deduced. Image processing methods, such as Zero-crossing Laplacian of Gaussian edge detection and region-filling, are used. The relative positions of the microgripper jaws, with respect to the gripper's pad, are determined by means of object recognition. Performed experiments confirm the success of the proposed sensor and verify that the measured deflections comply with the profile variations of the microgripper.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".