Abstract
A fuzzy neural network method based on T-S model was proposed for mobile robots to avoid obstacles. Using the proposed method, the obstacles in all environment types can be recognized, so the mobile robots could reach destination without collision. The new method not only has the advantage of fuzzy logic and neural network, but also has good self-study ability. First the data collected by 8 ultrasonic sensors were classified. Then the navigation algorithm based on T-S model was carried out. The test results show that the mobile robot using this fuzzy neural network can recognize the obstacles in all environment types, decide its action, and then arrive at destination after 231 seconds averagely in ten tests. It is faster than the mobile robot using BP neural network which takes 239 seconds
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© 2008 Springer-Verlag Berlin Heidelberg
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He, K., Gao, Y., Sun, H. (2008). A Fuzzy Neural Network Based on T-S Model for Mobile Robots to Avoid Obstacles. In: Xiong, C., Huang, Y., Xiong, Y., Liu, H. (eds) Intelligent Robotics and Applications. ICIRA 2008. Lecture Notes in Computer Science(), vol 5314. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88513-9_120
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DOI: https://doi.org/10.1007/978-3-540-88513-9_120
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-88512-2
Online ISBN: 978-3-540-88513-9
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