Interaction Mechanics Model for Rigid Driving Wheels of Planetary Rovers Moving on Sandy Terrain with Consideration of Multiple Physical Effects
Bibliographic record
Abstract
Predicting wheel‐terrain interaction with semiempirical models is of substantial importance for developing planetary wheeled mobile robots (rovers). Primarily geared toward the design of manned terrestrial vehicles, conventional terramechanics models do not provide the sufficient fidelity required for application on autonomous planetary rovers. To develop a high‐fidelity interaction mechanics model, in this study the physical effects of wheel lug, slip sinkage, wheel dimension, and load are analyzed based on experimental results, including wheel sinkage, drawbar pull, normal force, and moment, which are measured on a single‐wheel test bed. The mechanism of lug‐terrain interaction is investigated systematically to clarify the principle of increasing shear stress, conditions of forming successive shearing among adjacent lugs, and the influence on shear displacement of soil. A mathematical model for predicting the concentrated forces and torque of rigid wheels with lugs for planetary rovers moving on sandy terrain is derived by integrating the improved models of normal and shearing stress distributions. In addition to the wheel parameters, terrain parameters, and motion state variables, wheel‐terrain interaction parameters, such as the linear varying sinkage exponent, the soil displacement radius, and load effect parameters, were proposed and explicitly included in the model. In the single‐wheel experiments, the slip ratio was increased approximately from 0.05 to 0.6, and the relative errors of the predicted results using the proposed model are less than 10% for all the wheels when compared with the experimental data. The proposed model has been used in the simulation of a four‐wheeled rover, and its effectiveness is evaluated by comparing the simulation results with experimental results.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".