A fuzzy logic‐based formation controller for wheeled mobile robots
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Bibliographic record
Abstract
Purpose This paper seeks to present a novel approach for formation control of non‐holonomic wheeled mobile robots (WMRs). The use of a general geometrical structure has led the considered robotic team form any desired configuration. Although various methodologies have been suggested for solving such formation control problem in the literature, the proposed kinematical method of the present investigation has several advantages in terms of its robustness, tracking performance, and superior energy consumption due to the fuzzy logic scheme developed. Design/methodology/approach In an attempt to make the follower robot to assume the proper orientation, a new concept is presented which defines an appropriate heading angle. This concept is based on the natural human behavior as corresponds to situations of tracking a certain trajectory. The proposed heading angle planner is based on a two‐stage fuzzy logic system, providing appropriate heading angles for the mobile robot at each instant. In order to adjust the linear/angular velocity of the robots then, two further fuzzy controllers are devised. Findings The results obtained from the computer simulation studies reveal the merits as well as effectiveness of the proposed method for formation control of a group of WMRs in the presence of usual control input constraints, noisy sensor data, and external disturbances. Originality/value A novel method based on a fuzzy leader‐follower method is presented for the formation control of a group of robots.
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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 | 0.001 | 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 | 0.001 | 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