Novel calibration method for robotic bottom-up vat polymerization additive manufacturing systems
Why this work is in the frame
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Bibliographic record
Abstract
This article presents a new affordable calibration method for a 7-axis robotic system used for vat polymerization 3D printing. The method employs three metrology elements: a calibration robot end-effector with three precision balls, a measurement probe composed of three linear gauges, and, notably, a kinematic coupling allowing the precise positioning of the probe onto the resin tank in three locations. The robotic system comprises a Mecademic Meca500 6-axis industrial robot mounted on a Zaber X-LRQ300AP linear guide. The calibration method consists of automatically aligning the centers of each of the three precision balls with the probe origin. This alignment is performed with different robot joint angles and linear guide displacements, and for all three locations of the probe. After calibration, the relative accuracy of the 7-axis robotic system with respect to the resin tank, as validated using a laser tracker, is improved from 1.272 mm to 0.271 mm, which is comparable to what can be achieved with significantly more expensive metrology equipment. • A new calibration method for a vat polymerization 3D printing robotic system is proposed. • The method is based on a 3D probe, mounted on the resin tank via a Maxwell coupling. • A calibration end-effector with precision balls is also used. • The method is validated in 573 arbitrary robot joint sets using a laser tracker. • The mean position error of the 7-axis robot system is reduced to 0.271 mm.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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