A COOPERATIVE MOBILE ROBOT TASK ASSIGNMENT AND COVERAGE PLANNING BASED ON CHAOS SYNCHRONIZATION
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Bibliographic record
Abstract
In this paper, we propose a cooperative task assignment and coverage planning for mobile robots based on chaos synchronization. The chaotic mobile robot implies that the robot controller that drives a chaotic motion is characterized by topological transitivity and sensitive dependence on initial conditions. Due to the topological transitivity, the chaotic mobile robot is guaranteed to scan a workspace completely and the robot requires neither a map of the workspace nor a global motion plan. Chen and Lorenz systems are used to generate chaotic motion in this work. Cooperative multirobot systems can operate faster with higher efficiency and better reliability than a single robot system. By synchronizing the chaotic robot controllers, effective cooperation can be achieved. The performance of the cooperative chaotic mobile robots can be attributed to the use of deterministic dynamical systems and extended Kalman filter for chaos synchronization. Computer simulations illustrate the effectiveness of the proposed approach.
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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