Leader follower based formation control strategies for nonholonomic mobile robots: Design, implementation and experimental validation
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Bibliographic record
Abstract
This paper proposes novel formation maintenance strategies for multiple nonholonomic mobile robots based on nonholonomic trajectory tracking techniques and dynamic feedback linearization. It also presents experimental results for formation stability and noise tolerance of the proposed and existing leader-follower based controllers using physical P3AT robots. The research focusses only on the problem of formation maintenance by multiple nonholonomic mobile robots. Two types of formation maintenance controllers are developed by transforming the follower robot's motion in to separate trajectory tracking tasks and then by applying existing nonholonomic trajectory tracking techniques. A third controller is developed through the use of dynamic feedback linearization. The proposed systems are implemented in physical P3AT type mobile robots and real-world experimental results are shown to compare the formation accuracy and the stability of these controllers.
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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 | 0.000 | 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 | 0.001 |
| 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 it