Intelligent Following Car Based on Dual Detection Positioning Using Ultrasonic and Camera
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
To achieve real-time positioning of the target object for given tasks, a smart car system is designed using STM32F407 as the core control unit, mainly relying on ultrasonic sensors for detection and supplemented by camera detection for target locating and tracking. The ultrasonic sensor module is used as the main device for target information collection and transmission, and the distance difference between the two modules and the follow-up object is used to determine the target position. Meanwhile, the camera module is used for accurate positioning of the target, and algorithms such as Kalman filtering and PID closed-loop control are used to achieve interaction between the two detection modules and intelligent following. By doing so, the system can always maintain a distance from the target person and provide timely assistance as needed.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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