3928 Emergence of Objective Behavior with High-Speed Approaching Obstacle Avoidance of an Autonomous Mobile Robot by Learning with Subsumption Architecture

2005 ◽  
Vol 2005.7 (0) ◽  
pp. 247-248
Author(s):  
Yoshihiko KAWAZOE ◽  
Mitsuo IKEDA
Keyword(s):  
Mobile Robot ◽  
Obstacle Avoidance ◽  
High Speed ◽  
Autonomous Mobile Robot ◽  
Subsumption Architecture

Improved Wall-following Driving for Robot Operating System-based High-speed Autonomous Mobile Robot

2019 ◽  
Vol 28 (3) ◽  
pp. 156-165
Author(s):  
Seunghan Han ◽  
Yongrae Choi ◽  
Jaepil Yang ◽  
Hyungjun Hwang ◽  
Kihun Kim ◽  
...  
Keyword(s):  
Operating System ◽  
Mobile Robot ◽  
High Speed ◽  
Autonomous Mobile Robot ◽  
Robot Operating System ◽  
Wall Following

Practical Education Curriculum for Autonomous Mobile Robot (Project Learning Program for School Based on Subsumption Architecture)

2011 ◽  
Vol 23 (5) ◽  
pp. 684-700 ◽  
Author(s):  
Yoshihiko Kawazoe ◽  
◽  
Masaki Mitsuoka ◽  
Sho Masada
Keyword(s):  
Mobile Robot ◽  
Real World ◽  
Strong Nonlinearity ◽  
Autonomous Mobile Robot ◽  
Learning Program ◽  
Subsumption Architecture ◽  
The Real ◽  
Emotional Appeal ◽  
School Based ◽  
Autonomous Machine

There are presently no robots around us in our society if we define a robot as an autonomous machine working in the arena of offices, homes, disaster sites, etc., not in factories. Mechatronics, dynamics, and robotics involving humans are a world of strong nonlinearity. This paper investigates the approach to the emergence of the target behavior of an autonomous mobile robot by learning with Subsumption Architecture (SA) to break through the problems of the conventional robotics with the SMPA (Sense-Model-Plan-Act) framework in the real world. It has showed the way things are learned in the real world with SA and has been developed into a practical curriculum for education as an introduction to robotics that has an intellectual and emotional appeal.

Research on Navigation and Obstacle Avoidance Algorithm for Autonomous Mobile Robot in Narrow Area

2011 ◽  
Vol 464 ◽  
pp. 204-207
Author(s):  
Huan Xun Li ◽  
Jun Jie Shen ◽  
Shuai Guo
Keyword(s):  
Mobile Robot ◽  
Real Time ◽  
Obstacle Avoidance ◽  
Extraction Method ◽  
Field Method ◽  
Autonomous Mobile Robot ◽  
Environment Modeling ◽  
Feature Extraction Method ◽  
Potential Field Method ◽  
Narrow Area

In order to improve the accuracy and security when autonomous mobile robot moves in narrow area, a real-time navigation and obstacle avoidance algorithm is put forward. The feature extraction method is used to search for the path points, and the angle potential field method is used to search for the target angle. Based on the two methods more accurate environment modeling and navigation for mobile robot in narrow area is realized. The algorithm has been used successfully in the household robot, and the experiment results show it’s accurate and real-time.

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