Multi-functional capacitive proximity sensing system for industrial safety applications
Why this work is in the frame
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Bibliographic record
Abstract
This paper presents a capacitive sensing system, addressing the issue of collision avoidance in partially modelled or unknown robot-assisted industrial environment by means of object distance measurement, motion tracking, and surface profile detection. The sensor consists of a mesh of multiple electrodes, a digital control module, a capacitance to digital converter, and a data processing module. The mesh is composed of 16 metal squares organized to form a 4×4 capacitor matrix. The electrode connections within the matrix can be reconfigured at run time by the digital control logic to provide multiple sense functionalities. Statistical regression models are applied to derive the distance and track the motion. A machine learning algorithm (Support Vector Machine, SVM) is applied to measured data to classify surface profiles. The fabricated sensing system has the ability of detecting objects at distances up to 20 cm from the sensor, and shows accuracy over 90% in profile recognition.
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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 | 0.000 |
| 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 it