Laser Range Finder Applying in Motion Control System of Mobile Robots

2009 ◽  
Author(s):  
Jr-Hung Guo ◽  
Kuo-Lan Su ◽  
Chung-Chieh Wang ◽  
Chia-Ju Wu
Keyword(s):  
Control System ◽  
Mobile Robots ◽  
Motion Control ◽  
Laser Range Finder ◽  
Range Finder ◽  
Motion Control System ◽  
Laser Range

Ultrasonic sensor system for the uses in intelligent motion control system of a mobile robots group

2010 ◽  
Vol 7 ◽  
pp. 109-117
Author(s):  
O.V. Darintsev ◽  
A.B. Migranov ◽  
B.S. Yudintsev
Keyword(s):  
Control System ◽  
Mobile Robot ◽  
Mobile Robots ◽  
Motion Control ◽  
High Speed ◽  
Ultrasonic Sensor ◽  
Sensor System ◽  
Motion Control System ◽  
Speed Sensor ◽  
Working Space

The article deals with the development of a high-speed sensor system for a mobile robot, used in conjunction with an intelligent method of planning trajectories in conditions of high dynamism of the working space.

Motion planning for mobile robots using a laser range finder

2009 ◽  
Vol 14 (2) ◽  
pp. 257-261 ◽  
Author(s):  
Jr-Hung Guo ◽  
Kuo-Lan Su ◽  
Chia-Ju Wu ◽  
Sheng-Ven Shiau
Keyword(s):  
Motion Planning ◽  
Mobile Robots ◽  
Laser Range Finder ◽  
Range Finder ◽  
Laser Range

scholarly journals Furniture Model Creation Through Direct Teaching to a Mobile Robot

2008 ◽  
Vol 20 (2) ◽  
pp. 213-220 ◽  
Author(s):  
Kimitoshi Yamazaki ◽  
◽  
Takashi Tsubouchi ◽  
Masahiro Tomono ◽  
◽  
...  
Keyword(s):  
Mobile Robot ◽  
Mobile Robots ◽  
Real Life ◽  
Experimental Results ◽  
Sensor Data ◽  
Small Object ◽  
Laser Range Finder ◽  
Range Finder ◽  
Laser Range ◽  
Direct Teaching

In this paper, a modeling method to handle furniture is proposed. Real-life environments are crowded with objects such as drawers and cabinets that, while easily dealt with by people, present mobile robots with problems. While it is to be hoped that robots will assist in multiple daily tasks such as putting objects in into drawers, the major problems lies in providing robots with knowledge about the environment efficiently and, if possible, autonomously.If mobile robots can handle these furniture autonomously, it is expected that multiple daily jobs, for example, storing a small object in a drawer, can be performed by the robots. However, it is a perplexing process to give several pieces of knowledge about the furniture to the robots manually. In our approach, by utilizing sensor data from a camera and a laser range finder which are combined with direct teaching, a handling model can be created not only how to handle the furniture but also an appearance and 3D shape. Experimental results show the effectiveness of our methods.

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