Dynamic Path Tracking of Industrial Robots With High Accuracy Using Photogrammetry Sensor
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Bibliographic record
Abstract
In this paper, a practical dynamic path tracking (DPT) scheme for industrial robots is presented. The DPT scheme is a position-based visual servoing to realize three-dimensional dynamic path tracking by correcting the robot movement in real time. In the traditional task-implementation mode for industrial robots, the task planning and implementation are taught manually and hence the task accuracy largely depends on the repeatability of industrial robots. The proposed DPT scheme can realize automatic preplanned task and improve the tracking accuracy with eye-to-hand photogrammetry measurement feedback. Moreover, an adaptive Kalman filter is proposed to obtain smooth pose estimation and reduce the influence caused by image noise, vibration, and other uncertain disturbances. Due to high repeatability of the photogrammetry sensor, the proposed DPT scheme can achieve a high path tracking accuracy. The developed DPT scheme can be seamlessly integrated with the industrial robot controller and improve the robot's accuracy without retrofitting with high-end encoder. By using C-track 780 from Creaform as the photogrammetry sensor, the experimental tests on Fanuc M20-iA with the developed DPT scheme demonstrate the tracking accuracy is significantly improved (±0.20 mm for position and ±0.10 deg for orientation).
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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