DEVELOPMENT OF TRACKING SYSTEM FOR MOBILE ROBOT USING IMAGE RECOGNITION ALGORITHMS
Bibliographic record
Abstract
In this paper, an intelligent mobile robot using image processing technology is developed. The mobile robot contains an image system, a loading platform, a balance control system, a PC-based controller, four ultrasonic sensors and a power system. We develop a PC-based control system for image processing and path planning. The mobile robot can track a moving target and adjust the loading platform by the balance control system simultaneously. The image processing based on OpenCV uses two different tracking methods to track moving targets: MTLT (Match Template Learning Tracking) and TLD (Tracking, Learning and Detection). The efficiency of both methods for tracking the moving target on the mobile robot is compared here. The balance control system, with a HOLTEK Semiconductor Company’s HT66F Series 8-bit microprocessor as the processor, uses the PID control law according to the feedback signals of the inclinometer sensor to control the balance level of the loading platform.
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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".