Constellation: a Multi-User Interface for Remote Drone Tours
Bibliographic record
Abstract
Remotely controlled camera drones can support live, dynamic, and interactive virtual tours for travelers to overcome distance, expense, and health barriers. Yet, assigning one drone to one traveler may incur unnecessary waste of resources, and an abundance of concurrent drones raises safety concerns. While sharing the input and output of a single drone among multiple concurrent users can alleviate these limitations, standard control sharing protocols, such as turn-taking, are often inefficient. We present Constellation, a multi-user drone control system that synthesizes diverse user goals and generates efficient flight paths for the group. It supports point-of-interest specification on both static 3D environmental maps and live camera views. The generated paths minimize all users’ total extra waiting time. A web-based study with 16 participants show that Constellation could help groups navigate to their points-of-interest faster in comparison to the turn-taking baseline.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".