Realization of Consensus with Collision and Obstacle Avoidance in an Unknown Environment for Multiple Robots
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, we present a fuzzy logic-based control approach for the collision avoidance of a multi-robot system. A simple and continuous-time consensus law is implemented to achieve the rendezvous of the multiple mobile robot agents. A fuzzy logic-based controller is designed over a potential field method, as fuzzy algorithms are often robust and are not very sensitive to changing environments. Fuzzy logic is also useful for unknown and semi-unstructured environments. The algorithms are applicable to a general N-robot system and they are applied to three robots which are available in the host lab. Detailed information on the real-time implementation of the algorithm on three Pioneer mobile robots are presented. We have included simulations and experiments carried out to verify the effectiveness of our approach in this paper.
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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 | 0.000 |
| 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 it