Stereo vision algorithm for robotic assembly operations
Why this work is in the frame
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Bibliographic record
Abstract
A stereo vision Linear Triangulation (LT) algorithm can be utilized in space robotics assembly operations. The LT algorithm recovers the relative orientation and translation (pose) of objects marked with high contrast targets using two or more pinhole charge-coupled device (CCD) cameras. The cameras view a set (including a disjoint set) of targets measured with respect to the same point in space. This study evaluates the theoretical accuracy of the LT algorithm, its benefits and performance. The introduction of a third camera into the vision system envelope is also examined and discussed. Experiments indicated that most accuracy in pose estimation is gained by the first 15-25 degrees of camera separation, and then the decrease in values of the covariance matrix elements stabilizes. We compare the numerical data for singe, two-camera and threecamera cases using extensive experiments on simulated images.
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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