Waiting with Jose, a vision-based mobile robot
Why this work is in the frame
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Bibliographic record
Abstract
Jose is a visually guided autonomous robotic waiter. He circulates around a room populated by groups of people, politely serving appetizers to humans. The serving task combines elements of robotics with human computer interaction, challenging control architecture with multiple task integration. This paper describes our purely vision-based approach to this task. Methods for mapping, localization and navigation are presented and discussed, including issues of safety for both robots and humans. Our work on human-robot interaction is covered, as well as our solutions to various tasks specific to serving food. We present results of our methods from sample experiments in our laboratory. We further discuss our experiences at the 2001 AAAI mobile robot "Hors D'oeuvres Anyone?" competition, at which Jose took first prize.
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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