Stereo vision based swing angle sensor for mining rope shovel
Why this work is in the frame
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Bibliographic record
Abstract
An easily retrofittable stereo vision based system for quick and temporary measurement of a mining shovel's swing angle is presented. The stereo camera is mounted externally to the upper swingable shovel house, with a clear view of the shovel's lower carbody. As the shovel swings from its 0° swing angle position, the camera revolves with the shovel house, seeing differing views of the carbody. In real-time, the camera position is tracked, which in turn is used to calculate the swing angle. The problem was solved using the Simultaneous Localization and Mapping (SLAM) approach in which the system learns a map of 3D features on the carbody while using the map to determine the camera pose. The contribution includes a locally maximal Harris corner selection technique and a novel use of 3D feature clusters as landmarks, for improving the robustness of visual landmark matching in an outdoor environment. Results show that the vision-based sensor has a maximum error of +/- 1° upon map convergence.
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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) | 0.000 | 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