Problem formulation for path tracking automation of low speed articulated vehicles
Bibliographic record
Abstract
The paper concerns the problem of path tracking control in the class of vehicles made up of two units with an articulation between the two. Each unit has two fixed (nonsteerable) wheels. Steering action is, thus, performed by changing the angle between the front and rear units. Such a vehicle is used for transfer of ore inside the relatively narrow and restricted underground mine galleries. The articulation in the middle helps also for better capability in curve negotiation. In operation, this vehicle usually moves with a low speed because of the environment. As a result, a number of issues, such as dynamic stability and aerodynamic forces which are important to road vehicles, do not come into effect. Furthermore, as far as the path tracking automation is concerned, the dynamics of the vehicle and tire deformation have little effect and can be neglected. Analysis and formulation of the path tracking problem, thus, can be based on the kinematics only. In this paper the control problem is formulated and verified. The synthesis of a feedback system to govern the steering action, then, becomes possible.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".