DOCUMENT DELIVERY ROBOT BASED ON IMAGE PROCESSING AND FUZZY CONTROL
Bibliographic record
Abstract
The objective of this study is to integrate image processing, pattern recognition, RFID, and fuzzy theory into an omnidirectional wheeled mobile robot for receiving and delivering documents between rooms. In image pre-processing, the Hue-Saturation-Lightness color space is applied to avoid light interference, and then grayscale image threshold is used to obtain binary image. The median filter is utilized to filter the noises of speckle and salt-and-pepper, so color segmentation is then applied to capture desired color for tracking control. Pattern recognition is performed by the Adaptive Resonance Theory. RFID reader and room tag is used to verify the room number of the destination so that the recognition error from image processing can be avoided. Fuzzy theory is implemented into an omnidirectional wheeled mobile robot control design for driving the wheels of the robot. Experimental results show that the proposed control scheme can make the omnidirectional mobile robot move to destination, receive and deliver documents between offices.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".