Why robots should use fuzzy mathematical morphology

Mobile robots must represent and reason about spatial knowledge acquired from sensor data which are inherently approximate and uncertain. While techniques based on fuzzy sets are increasingly used in this domain, the use of these techniques often rests on intuitive grounds. In this paper, we show that fuzzy mathematical morphology, a theory often used in image processing but mostly ignored in the robotic tradition, can provide a well grounded approach to the treatment of imprecise spatial knowledge in robotics

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