Effect of Redundant Actuation on the Mobility of Wheeled Robots on Unstructured Terrain
Bibliographic record
Abstract
Improving the mobility of wheeled robots operating on unstructured terrain is a challenging task that can be approached in different ways. Enhanced mobility results in the vehicle being able to successfully negotiate slopes and obstacles, expanding the range of missions that can be undertaken and reducing the risk of losing or damaging the robot. This goal is directly related to optimizing the way in which traction force is developed at the wheel-terrain contact interfaces. Several strategies to achieve this objective, including traction control algorithms and reconfiguration, have been proposed in the literature. In this work, internal actuation is explored as a means to obtain better mobility on soft and irregular terrain. The use of this technique is demonstrated with a rover prototype in three maneuvers, namely flat soft terrain traverse, slope climbing on soft terrain, and negotiation of a step obstacle. Results show that redundant actuation can be used to improve the behavior of the vehicle, for optimum mobility on soft and irregular terrain.
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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 | 0.001 |
| 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) | 0.001 | 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 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".