Development of Autonomous Mobile Robot “MML-05” Based on i-Cart Mini for Tsukuba Challenge 2015
Author(s) -
Tomoyoshi Eda,
Tadahiro Hasegawa,
Shingo Nakamura,
Shin’ichi Yuta
Publication year - 2016
Publication title -
journal of robotics and mechatronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.257
H-Index - 19
eISSN - 1883-8049
pISSN - 0915-3942
DOI - 10.20965/jrm.2016.p0461
Subject(s) - occupancy grid mapping , odometry , mobile robot , robot , computer science , artificial intelligence , computer vision , grid , matching (statistics) , grid reference , geography , mathematics , statistics , geodesy
[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.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom