Abstract
This work develops a knowledge based system to autonomous navigation using Fuzzy Cognitive Maps (FCM). A new variant of FCM, named Dynamic-Fuzzy Cognitive Maps (D-FCM), is used to model decision tasks and/or make inference in the robot or mobile navigation. Fuzzy Cognitive Maps is a tool that model qualitative structured knowledge through concepts and causal relationships. The proposed model allows representing the dynamic behavior of the mobile robot in presence of environment changes. A brief review of correlated works in the navigation area by use of FCM is presented. Some simulation results are discussed highlighting the ability of the mobile to navigate among obstacle (navigation environment). A comparative with Fuzzy Logic and future works are also addressed.
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Mendon, M., Chrun, I.R., de Arruda, L.V.R., Papageorgiou, E.I. (2013). Autonomous Navigation Applying Dynamic-Fuzzy Cognitive Maps and Fuzzy Logic. In: Papadopoulos, H., Andreou, A.S., Iliadis, L., Maglogiannis, I. (eds) Artificial Intelligence Applications and Innovations. AIAI 2013. IFIP Advances in Information and Communication Technology, vol 412. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41142-7_22
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DOI: https://doi.org/10.1007/978-3-642-41142-7_22
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