VR Collide! Comparing Collision-Avoidance Methods Between Co-located Virtual Reality Users
Why this work is in the frame
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Bibliographic record
Abstract
We present a pilot study comparing visual feedback mechanisms for preventing physical collisions between co-located VR users. These include Avatar (a 3D avatar in co-located with the other user), BoundingBox (similar to HTC's "chaperone"), and CameraOverlay (live video feed overlaid on the virtual environment). Using a simulated second user, we found that CameraOverlay and Avatar had the fastest travel time around an obstacle, but BoundingBox had the fewest collisions at 0.07 collision/trial versus 0.2 collisions/trial for Avatar and 0.4 collisions/trial for CameraOverlay. However, subjective participant impressions strongly favoured Avatar and CameraOverlay over BoundingBox. Based on these results, we propose future studies on hybrid methods combining the best aspects of Avatar (speed, user preference) and BoundingBox (safety).
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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 | 0.002 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| 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