Vision Based In-Process Inspection for Robotic Automated Riveting
Bibliographic record
Abstract
As part of an ongoing collaborative research project between The University of Nottingham and Bombardier Aerospace a pair of end-effectors have been developed that allow solid riveting of aircraft fuselage panels to be performed using conventional robots. This paper describes the development and performance testing of a compact process monitoring system and its integration into the riveting end-effector and testing. The developed process monitoring system is based around a miniature CCD camera combined with a novel structured lighting system. The combination of the structured lighting system with image processing techniques means that good quality images of the drilled and countersunk holes and rivets can be obtained despite the confined environment and highly reflective materials involved. The impact of the system on the overall cycle time is also minimised. The system has been successfully used to check the circularity and dimensions of the countersink of a hole drilled by the system in an Regional Jet fuselage panel and to check for the presence of any marking on the panel surface.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".