2P2-D15 An environment Recognition System for a wheel type mobile robot with rough terrain movement : Second Report : Controller Selection depending on Environment Recognition System and Classification of Un-learned Environment

2008 ◽  
Vol 2008 (0) ◽  
pp. _2P2-D15_1-_2P2-D15_4
Author(s):  
Atsushi KANDA ◽  
Masanori SATO ◽  
Kazuo ISHII
Keyword(s):  
Mobile Robot ◽  
Recognition System ◽  
Rough Terrain ◽  
Environment Recognition

3-D Scan Matching for Mobile Robot Localization over Rough Terrain

2019 ◽  
Vol 139 (9) ◽  
pp. 1041-1050
Author(s):  
Hiroyuki Nakagomi ◽  
Yoshihiro Fuse ◽  
Hidehiko Hosaka ◽  
Hironaga Miyamoto ◽  
Takashi Nakamura ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Rough Terrain ◽  
Robot Localization ◽  
Scan Matching ◽  
Mobile Robot Localization

Vision based environment recognition for mobile robot in irregular ground

2007 ◽  
Author(s):  
Shin'ya Okazaki ◽  
Takayuki Tanaka ◽  
Syun'ichi Kaneko ◽  
Akihiko Matsushita
Keyword(s):  
Mobile Robot ◽  
Environment Recognition

ALGORITHMS FOR FINGERPRINT CLASSIFICATION

2021 ◽  
Vol 335 (1) ◽  
pp. 39-44
Author(s):  
D. Lebedev ◽  
A. Abzhalilova
Keyword(s):  
Neural Network ◽  
Gabor Filter ◽  
Recognition System ◽  
Personal Identification ◽  
External Object ◽  
Biometric Identification ◽  
Fingerprint Classification ◽  
Combined Application ◽  
Traditional Approaches

Currently, biometric methods of personality are becoming more and more relevant recognition technology. The advantage of biometric identification systems, in comparison with traditional approaches, lies in the fact that not an external object belonging to a person is identified, but the person himself. The most widespread technology of personal identification by fingerprints, which is based on the uniqueness for each person of the pattern of papillary patterns. In recent years, many algorithms and models have appeared to improve the accuracy of the recognition system. The modern algorithms (methods) for the classification of fingerprints are analyzed. Algorithms for the classification of fingerprint images by the types of fingerprints based on the Gabor filter, wavelet - Haar, Daubechies transforms and multilayer neural network are proposed. Numerical and results of the proposed experiments of algorithms are carried out. It is shown that the use of an algorithm based on the combined application of the Gabor filter, a five-level wavelet-Daubechies transform and a multilayer neural network makes it possible to effectively classify fingerprints.

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