Negotiating Corners With Teleoperated Mobile Robots With Time Delay
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Bibliographic record
Abstract
In this paper, we present the summary of results from a teleoperation study to assess the application of a mobile robot cornering law with the inclusion of a time delay on the returned video stream. The intent is to demonstrate this application to an analogous scenario like teleoperating from Earth a rover at the south Lunar pole. The first experiment compared course completion times for outdoor driving circuits in ideal lighting without time delay, ideal lighting with time delay, and in darkness with time delay and a low-angled spotlight. The second experiment studied cornering times for various time delays and lighting conditions in an indoor setting. The results show that teleoperating a mobile robot with the presence of time delay still complies with the previously developed cornering law. The combined results from the cornering study and the outdoor driving course are interpreted to show that the total time to complete a driving course with a time-delayed video can be predicted based on a known number of turns.
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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 | 0.001 | 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 | 0.001 |
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