An autonomous mobile robot with fuzzy obstacle avoidance behaviors and a visual landmark recognition system
Why this work is in the frame
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Bibliographic record
Abstract
Multi-sensor fusion has been a hot topic in the field of robotics. Inspired by the modern philosophy's spirit, the behavior-based systems interact with the real world directly. In this study, a fully autonomous mobile robot is developed that extracts all its knowledge from physical sensors and expresses all its goals and desires as physical action to affect its environment. The control software implements behavior-based artificial intelligence, where the coordination between various sensors are realized by layers of several simple and primitive behaviors similar to those observed in animals. In the developed mobile robot, each module itself generates behaviors. Behaviors corresponding to different sensors have different priorities, where the vision system has the lowest priority, and the ultrasonic sensors and bumper sensors have higher priority. The effectiveness of the developed system is demonstrated by experimental studies.
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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 | 0.001 |
| 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