A practical approach to control and self-localization of Persia omni directional mobile robot
Why this work is in the frame
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Bibliographic record
Abstract
Omni directional mobile robots have been popularly employed in several applications especially in soccer player robots in Robocup competitions. However, control and self-localization of omni directional mobile robots are important issues and different teams in the Robocup competitions have used different techniques to tackle it. Since it is very complicated to calculate the omni directional system transfer function as in classic control, a simplified model of the system would be helpful for estimating the PID coefficients of the robots' position and orientation control. The vision-based self-localization combined with the odometry system enables us to have a robust self-localization method. The findings have been tested in the Robocup competition field using three Persia middle size omni directional robots.
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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