Abstract
In autonomous transport systems, it is useful to be able to continue interrupted traffic after removing the obstacle that caused deviations from the route. This article describes a control model in which cognitive functions, such as context and attention are embedded. The fuzzy situational control model of an autonomously moving machine along a route with obstacles is expanded by tracking context and switching attention mechanisms. Additionally, it describes a knowledge representation about the route, the surrounding space and how to avoid collisions with obstacles.
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