2A2-E14 An Environment Recognition System for a Wheel Type Mobile Robot with Rough Terrain Movement : Fourth Report: Installation of Self-Organizing Template making method

2010 ◽  
Vol 2010 (0) ◽  
pp. _2A2-E14_1-_2A2-E14_4
Author(s):  
Atsushi KANDA ◽  
Kazuo ISHII ◽  
Masanori SATO
Keyword(s):  
Mobile Robot ◽  
Recognition System ◽  
Rough Terrain ◽  
Fourth Report ◽  
Environment Recognition ◽  
Self Organizing

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

scholarly journals Dynamic Gesture Recognition System with Gesture Spotting Based on Self-Organizing Maps

2021 ◽  
Vol 11 (4) ◽  
pp. 1933
Author(s):  
Hiroomi Hikawa ◽  
Yuta Ichikawa ◽  
Hidetaka Ito ◽  
Yutaka Maeda
Keyword(s):  
Real Time ◽  
Gesture Recognition ◽  
Weight Vector ◽  
Recognition System ◽  
Self Organizing Map ◽  
Self Organizing Maps ◽  
Time Dynamic ◽  
System Input ◽  
Self Organizing ◽  
Gesture Spotting

In this paper, a real-time dynamic hand gesture recognition system with gesture spotting function is proposed. In the proposed system, input video frames are converted to feature vectors, and they are used to form a posture sequence vector that represents the input gesture. Then, gesture identification and gesture spotting are carried out in the self-organizing map (SOM)-Hebb classifier. The gesture spotting function detects the end of the gesture by using the vector distance between the posture sequence vector and the winner neuron’s weight vector. The proposed gesture recognition method was tested by simulation and real-time gesture recognition experiment. Results revealed that the system could recognize nine types of gesture with an accuracy of 96.6%, and it successfully outputted the recognition result at the end of gesture using the spotting result.

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
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