An algorithm for haptically rendering objects described by point clouds
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
In this paper, we present an algorithm to haptically render point clouds without first building a corresponding polygonal mesh. Our algorithm deduces necessary surface information, which is inherently unavailable in point clouds, by building neighborhood knowledge into each surface point, and also by using bounding boxes to imply surfaces in place of the voids found between neighboring points in the point cloud. Collision detection in our approach is a matter of checking line segments (representing the motion of the haptic probe) against the aforementioned bounding boxes, while force response (3-DOF) is based on our adaptation to point clouds of the standard god-object/proxy method. This adaptation implies the required constraint surfaces from the cloud’s surface points by exploiting their knowledge of their neighboring points. Our algorithm has a runtime that is highly insensitive to (but not independent of) the complexity of the point cloud, and is designed to relay all the coordinate information found in the point cloud to the extent allowed by the haptic device’s resolution.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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