UAV, come to me: End-to-end, multi-scale situated HRI with an uninstrumented human and a distant UAV
Bibliographic record
Abstract
We present the first demonstration of end-to-end far-to-near situated interaction between an uninstrumented human user and an initially distant outdoor autonomous Unmanned Aerial Vehicle (UAV). The user uses an arm-waving gesture as a signal to attract the UAV's attention from a distance. Once this signal is detected, the UAV approaches the user using appearance-based tracking until it is close enough to detect the human's face. Once in this close-range interaction setting, the user is able to use hand gestures to communicate its commands to the UAV. Throughout the interaction, the UAV uses colored-light-based feedback to communicate its intent to the user. We developed this system to work reliably with a low-cost consumer UAV, with only computation off-board. We describe each component of this interaction system, giving details of the depth estimation strategy and the cascade predictive flight controller for approaching the user. We also present experimental results on the performance of the complete system and its individual components.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".