Abstract
This paper focuses on the study of intelligent navigation techniques which are capable of navigating a mobile robot autonomously in unknown environments in real-time. We primarily focused on a soft computing-based control system of autonomous robot behaviour. The soft computing methods included artificial neural networks and fuzzy logic. Using them, it was possible to control autonomous robot behaviour. Based on defined behaviour, this device was able to deduce a corresponding reaction to an unknown situation. Real robotic equipment was represented by a Lego Mindstorms EV3 robot. The outcomes of all experiments were analysed in the conclusion.
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Acknowledgments
The research described here has been financially supported by the University of Ostrava grant SGS05/PRF/2019.
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Volná, E., Kotyrba, M., Bradac, V. (2020). Soft Computing-Based Control System of Intelligent Robot Navigation. In: Nguyen, N., Jearanaitanakij, K., Selamat, A., Trawiński, B., Chittayasothorn, S. (eds) Intelligent Information and Database Systems. ACIIDS 2020. Lecture Notes in Computer Science(), vol 12034. Springer, Cham. https://doi.org/10.1007/978-3-030-42058-1_32
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