Development of an Autonomous Mobile Robot with Several Sensors using Neuro-Fuzzy Control Based on Server/Client Model

2008 ◽  
Vol 3 (2) ◽  
pp. 212-221 ◽  
Author(s):  
Masashi Ohchi ◽  
Tatsuya Furukawa ◽  
Hisao Tokushima ◽  
Shinichi Sasaki
Keyword(s):  
Fuzzy Control ◽  
Mobile Robot ◽  
Autonomous Mobile Robot ◽  
Neuro Fuzzy

scholarly journals Neuro-fuzzy Control for Balancing a Two-wheel Mobile Robot

2016 ◽  
Vol 22 (1) ◽  
pp. 40-45
Author(s):  
Young Jun Park ◽  
Seul Jung
Keyword(s):  
Fuzzy Control ◽  
Mobile Robot ◽  
Neuro Fuzzy

Path following behavior for an autonomous mobile robot using neuro-fuzzy controller

2013 ◽  
Vol 5 (3) ◽  
pp. 352-360 ◽  
Author(s):  
Lakhmissi Cherroun ◽  
Mohamed Boumehraz
Keyword(s):  
Mobile Robot ◽  
Fuzzy Controller ◽  
Path Following ◽  
Autonomous Mobile Robot ◽  
Neuro Fuzzy

Neuro-fuzzy control of a mobile robot

1999 ◽  
Vol 28 (1-3) ◽  
pp. 127-143 ◽  
Author(s):  
Jelena Godjevac ◽  
Nigel Steele
Keyword(s):  
Fuzzy Control ◽  
Mobile Robot ◽  
Neuro Fuzzy

scholarly journals Navigation Algorithm Using Fuzzy Control Method in Mobile Robotics

2016 ◽  
Vol 19 (1) ◽  
pp. 19-23 ◽  
Author(s):  
Vladimír Cviklovič ◽  
Martin Olejár ◽  
Dušan Hrubý ◽  
Zuzana Palková ◽  
Ondrej Lukáč ◽  
...  
Keyword(s):  
Fuzzy Control ◽  
Mobile Robot ◽  
Mobile Robotics ◽  
Control Method ◽  
Autonomous Mobile Robot ◽  
Navigation Algorithm ◽  
Heading Angle ◽  
Left And Right ◽  
Input Variables ◽  
Fuzzy Control Algorithm

The issue of navigation methods is being continuously developed globally. The aim of this article is to test the fuzzy control algorithm for track finding in mobile robotics. The concept of an autonomous mobile robot EN20 has been designed to test its behaviour. The odometry navigation method was used. The benefits of fuzzy control are in the evidence of mobile robot’s behaviour. These benefits are obtained when more physical variables on the base of more input variables are controlled at the same time. In our case, there are two input variables - heading angle and distance, and two output variables - the angular velocity of the left and right wheel. The autonomous mobile robot is moving with human logic.

scholarly journals MIMO Fuzzy Control for Autonomous Mobile Robot

2015 ◽  
Vol 3 (6) ◽  
pp. 65-70 ◽  
Author(s):  
Thoa T. Mac ◽  
Cosmin Copot ◽  
Robin De Keyser ◽  
Trung D. Tran ◽  
Thich Vu
Keyword(s):  
Fuzzy Control ◽  
Mobile Robot ◽  
Autonomous Mobile Robot
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