Analysis on Wheel–Ground Contact Load Characteristics of Unmanned Off-road Vehicles
Why this work is in the frame
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Bibliographic record
Abstract
The wheel-ground contact load characteristics of unmanned ground vehicles are an important foundation for vehicle design, structural parameter optimization, off-road performance evaluation, and control strategy formulation. The load characteristics of unmanned ground vehicles are mainly investigated based on traditional vehicle terramechanics theory, which cannot reflect wheel-ground contact. This study proposed a model integrated with qualitative theoretical analysis and quasi-quantitative simulation to evaluate wheel-ground contact load characteristics during the off-road movement of unmanned vehicles. Prediction and test models of system wheel contact load characteristics were built by multi-physical field coupling analysis. Flow and power characteristics during unilateral steering were discussed systematically through terramechanics theory. The accuracy of the models was verified by experiments. Results show that changes in the tire load affect the average stress on the ground contact surface of tire, which leads to the forward gravity center of the entire machine. The optimal combination of structural parameters under dynamic working conditions of the unmanned vehicles is determined based on multi-physics coupling analysis model to optimize the structural design. The load pressure of the system reaches 19.53 MPa in the accelerated start-up phase, and the error of simulation and test results is within 10%. This study provides tools for theoretical and simulation analysis for development of the optimized structure design and control strategy formulation of unmanned ground vehicles.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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