This paper presents a method for embedding human expert knowledge into a fuzzy logic controller. The method was developed while designing a fuzzy logic control system for an autonomous vehicle that utilized sparse sensor data for terrain classification. We will discuss the design for the fuzzy logic terrain classification system and use it as an example for explaining the embedding method.

In the example, a human expert classified terrain features from sensor data provided by a two-dimensional computer simulation. From the information derived from the expert, we developed both a classification system for the terrain features and a fuzzy logic rule base for the controller. The simulation, along with an optimization algorithm, was then used to train the fuzzy logic controller to match the human responses.

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