Fuzzy Cognitive Map Based Situation Assessment Framework for Navigation Goal Detection
Why this work is in the frame
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Bibliographic record
Abstract
Navigation goal detection in complex real world scenarios is challenging for autonomous mobile robots due to the uncertainty and ambiguity of their environments. This paper proposes a fuzzy cognitive map (FCM) based situation assessment framework (SAF) for mobile robot navigation goal detection. A given navigation goal is described with several sub-goals using prior knowledge. Based upon these sub-goals, the proposed SAF operates recursively on the navigation goal to verify it. The decision fusion system combines sensory information from multiple sensors to verify the sub-goals. The FCM, which is realized using fuzzy gamma fusion, is used as a high level reasoning engine. The navigation goals are verified based on the rules which connect sub-goals together and the goal assertion confidence of sub-goals which is decided using FCM inference. Experimental results demonstrate that the proposed framework can accurately decide the navigation goals in unknown environments based on the sensory information and expert knowledge.
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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