A 3D Irregular Packing Algorithm Using Point Cloud Data
Why this work is in the frame
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Bibliographic record
Abstract
The cutting and packing (C&P) problem has been extensively studied as it has a wide variety of applications in many industries. Good packing solutions can effectively reduce manpower and production costs. However, approaches for packing 3D irregular shaped items common in construction are very limited. In this paper, a heuristic algorithm to pack a set of irregular shaped items into a box-shaped container with the objective to maximize the contact area between objects has been proposed as one step required for alternative packing solutions. A 3D scanner is employed to obtain the geometric information of items. The heuristic algorithm determines the rotation and translation of each item, moves the objects into close proximity, and fits the objects together automatically using point cloud representation. This is a new approach. Experiment results show that the proposed approach has the potential to support good packing solutions of realistic items in a reasonable time.
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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 | 0.000 |
| 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) | 0.001 | 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