DOCUMENT DELIVERY ROBOT BASED ON IMAGE PROCESSING AND FUZZY CONTROL
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
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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