A fuzzy logic approach to reactive navigation of behavior-based mobile robots
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this paper, a novel fuzzy logic control system is developed for reactive navigation of a behavior-based mobile robot in dynamic environments. A combination of multiple sensors is equipped to sense the obstacles near the robot, the target location and the current robot speed. A fuzzy logic system with 48 fuzzy rules is designed, which consists of three behaviors: target seeking, obstacle avoidance and barrier following. The "symmetric indecision" problem is resolved by several mandatory-turn rules, while the "dead cycle" problem is resolved by a state memory strategy. Under the control of the proposed fuzzy logic model, the mobile robot can preferably "see" the environment around, and avoid static and moving obstacles automatically. The robot can generate reasonable trajectories toward the target in various situations without suffering from the "symmetric indecision" and the "dead cycle" problems. The effectiveness and efficiency of the proposed approach are demonstrated by simulation studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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