Visual Servoing of a Mobile Robot in Presence of Tilt Disturbances Using a Central Catadioptric Vision System
Bibliographic record
Abstract
Catadioptric vision systems have been studied in the realm of visual servoing of mobile and articulated robots for the past decade. They are considered superior to a single camera system because of their larger field of view and higher resolution. This paper presents a new calibration method to estimate the tilt of a mobile robot equipped with a central catadioptric vision system moving on rough terrains. The proposed approach is based on the spatial projection of a set of parallel lines onto the image plane of an orthographic camera linked with a parabolic mirror. A methodology was developed to estimate 3-axis orientation of the catadioptric camera mounted on a mobile robot through information obtained from the 2D image. Furthermore, a visual servoing strategy was developed to drive a mobile robot from a given configuration to a target configuration while accounting for tilt disturbances imposed by the terrain. The performance of the proposed method is evaluated via computer simulations.
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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) | 0.000 | 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 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".