1A2-I01 Autonomous mobile robot using the self-position estimation based on dynamic sensor selection(Localization and Mapping (1))

2013 ◽  
Vol 2013 (0) ◽  
pp. _1A2-I01_1-_1A2-I01_3
Author(s):  
Yoshinori Shimura ◽  
Yuichi Saikawa ◽  
Kazuyuki Morioka
Keyword(s):  
Mobile Robot ◽  
Position Estimation ◽  
Sensor Selection ◽  
The Self ◽  
Autonomous Mobile Robot ◽  
Localization And Mapping

SELF-POSITION ESTIMATION OF AUTONOMOUS MOBILE ROBOT THAT USES METALLIC LANDMARK

2010 ◽  
Author(s):  
HAJIME FUJII ◽  
YOSHINOBU ANDO ◽  
TAKASHI YOSHIMI ◽  
MAKOTO MIZUKAWA
Keyword(s):  
Mobile Robot ◽  
Position Estimation ◽  
Autonomous Mobile Robot

Development of Autonomous Mobile Robot “MML-05” Based on i-Cart Mini for Tsukuba Challenge 2015

2016 ◽  
Vol 28 (4) ◽  
pp. 461-469 ◽  
Author(s):  
Tomoyoshi Eda ◽  
◽  
Tadahiro Hasegawa ◽  
Shingo Nakamura ◽  
Shin’ichi Yuta
Keyword(s):  
Mobile Robot ◽  
Mobile Robots ◽  
The Self ◽  
Autonomous Mobile Robots ◽  
Autonomous Mobile Robot ◽  
Localization Method ◽  
Occupancy Grid ◽  
Grid Map ◽  
Local Grid ◽  
Occupancy Grid Map

[abstFig src='/00280004/04.jpg' width='300' text='Autonomous mobile robots entered in the Tsukuba Challenge 2015' ] This paper describes a self-localization method for autonomous mobile robots entered in the Tsukuba Challenge 2015. One of the important issues in autonomous mobile robots is accurately estimating self-localization. An occupancy grid map, created manually before self-localization has typically been utilized to estimate the self-localization of autonomous mobile robots. However, it is difficult to create an accurate map of complex courses. We created an occupancy grid map combining local grid maps built using a leaser range finder (LRF) and wheel odometry. In addition, the self-localization of a mobile robot was calculated by integrating self-localization estimated by a map and matching it to wheel odometry information. The experimental results in the final run of the Tsukuba Challenge 2015 showed that the mobile robot traveled autonomously until the 600 m point of the course, where the occupancy grid map ended.

1A2-D27 Research on self-position estimation of autonomous mobile robot that uses metallic landmark

2010 ◽  
Vol 2010 (0) ◽  
pp. _1A2-D27_1-_1A2-D27_3
Author(s):  
Hajime FUJII ◽  
Yoshinobu ANDO ◽  
Takashi YOSHIMI ◽  
Makoto MIZUKAWA
Keyword(s):  
Mobile Robot ◽  
Position Estimation ◽  
Autonomous Mobile Robot

Self-position estimation of an autonomous mobile robot with variable processing time

2010 ◽  
Vol 93 (11) ◽  
pp. 46-58
Author(s):  
Kae Doki ◽  
Naohiro Isetani ◽  
Akihiro Torii ◽  
Akiteru Ueda ◽  
Hirotsugu Tsutsumi
Keyword(s):  
Mobile Robot ◽  
Processing Time ◽  
Position Estimation ◽  
Autonomous Mobile Robot ◽  
Variable Processing
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