Viewpoint Tethering for Remotely Operated Vehicles: Effects on Complex Terrain Navigation and Spatial Awareness
Bibliographic record
Abstract
OBJECTIVE: The effect of viewpoint on the navigation of complex terrain and on spatial awareness was examined with the use of a simulated remotely operated vehicle. BACKGROUND: The ability to build terrain models in real time may soon allow remote vehicular control from any viewpoint. A virtual tether couples the viewpoint to the vehicle's position and orientation, but shows more of the terrain than a fully immersive egocentric display. In this sense, it provides visual momentum by providing a view that incorporates egocentric and exocentric qualities. METHOD: For this study, 12 participants navigated a simulated vehicle across complex virtual terrain using five different display viewpoints: egocentric, dynamic tether, rigid tether, 3-D exocentric, and 2-D exocentric. While navigating, participants had to avoid being seen by simulated enemy units. After the navigation task, participants' spatial awareness was assessed using a recognition task. RESULTS: The tethered displays minimized the time during which the participant's vehicle was visible to enemy positions. The egocentric display was more effective than exocentric displays (2-D or 3-D) for navigation, and the exocentric displays were more effective than egocentric for time seen during navigation and the recognition task. The tethered displays produced intermediate results for navigation and recognition. CONCLUSION: Viewpoint tethering produced the most effective displays for minimizing time seen, but tethered displays were less effective than egocentric and exocentric displays for navigation and recognition, respectively. APPLICATION: A tethered display is recommended for applications in which it is necessary to understand the relation of nearby locations to one's own location.
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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 | 0.001 | 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 | 0.000 |
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".