Trajectory determination for pipelines using an inspection robot and pipeline features
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Geographic trajectory of a pipeline is important information for pipeline maintenance and leak detection.Although accurate trajectory of a ground pipeline usually can be directly measured by using global positioning system technology, it is much difficult to determine trajectory for an underground pipeline where global positioning system signal cannot be received.In this paper, a new method to determine trajectory for an underground pipeline by using a pipeline inspection robot is proposed.The robot is equipped with a low-cost inertial measurement unit and odometers.The kinematic model, measurement model and error propagation model are established for estimating position, velocity and attitude of the robot.The path reconstruction algorithm for the robot is proposed to improve accuracy of trajectory determination based on pipeline features.The experiment is given to illustrate that the position errors of the proposed method are less than 40% of that of the standard extended Kalman filter.
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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 | 0.001 | 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