Sharing charging stations for long-term activity of autonomous robots
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
To operate over a long period of time, autonomous mobile robots must have the capability of recharging themselves whenever necessary. In addition to be able to find and connect to a power source, robots must also consider taking actions to preserve and share energy in an environment where energy is a limited resource. Coordination is then required to ensure the survival of the group and the accomplishment of the robots' tasks. This paper explores these issues by allowing robots to predict and reason about their energetic capabilities, as individuals and as a group. The approach described allows robots to determine when to recharge, when to change their activity level and how long they should recharge. Validation of the work is done in simulation to demonstrate the versatility of the approach for different numbers of robots and power sources. Experiments with Pioneer 2 robots are also reported.
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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