The methods of recognizing blurry and smudgy navigation path are studied by using fuzzy neural network for JLUIV-2 vision navigation intelligent vehicle. Two fuzzy neural network models are developed, one model has 5 layers, and uses normal distribution probability function as its fuzzy function, another model has 6 layers, and uses /spl pi/ function as its fuzzy function. The dynamic BP algorithm is used to train the two fuzzy neural networks. Experiments of the path recognizing and practical autonomous navigation are done by using JLUIV-2 intelligent vehicle. The results show that the two fuzzy neural networks can effectively recognize the blurry and smudgy navigation path.
Study on blurry and smudgy path recognition by fuzzy neural network
Intelligent Vehicle Symposium, 2002. IEEE ; 1 ; 160-165 vol.1
2002-01-01
409892 byte
Conference paper
Electronic Resource
English
Study on Blurry and Smudgy Path Recognition by Fuzzy Neural Network
British Library Conference Proceedings | 2003
|On high-speed rail´s beaten and blurry path
IuD Bahn | 2011
|NTIS | 2019
|NTRS | 2019
|Robustness of noisy and blurry images segmentation
British Library Online Contents | 2009
|