CAN-based Distributed Control for Autonomous Vehicles
Bibliographic record
Abstract
Through the work of researchers and the development of commercially available products, automated guidance has become a viable option for agricultural producers. One limiting factor of many commercially available technologies is that they only automate one function of an agricultural vehicle and that their control systems are proprietary to a single machine model. The objective of this project was to evaluate a controller area network (CAN bus) as the basis of an automated agricultural vehicle. The prototype system utilized several microcontroller-driven nodes to act as control points along a system wide CAN bus. Messages were transferred to the steering, transmission, and hitch control nodes from a task computer. The task computer utilized global positioning system data to determine the appropriate control commands. Infield testing demonstrated that each of the control nodes could be controlled simultaneously over the CAN bus. Results showed that the task computer adequately applied a feedback control model to the system and achieved guidance accuracy levels well within the desired range. Testing also demonstrated the system's ability to complete normal field operations such as headland turning and implement control.
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How this classification was reachedexpand
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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".