JRM Vol.25 No.1 pp. 25-37
doi: 10.20965/jrm.2013.p0025


Visual Localization for Mobile Robots Based on Composite Map

Hung-Hsiu Yu*, Hsiang-Wen Hsieh*, Yu-Kuen Tasi*,
Zhi-Hung Ou**, Yea-Shuan Huang**, and Toshio Fukuda***

*Intelligent Robotics Division, Mechanical and System Laboratory, Industrial Technology Research Institute, 195, Sec. 4, Chung Hsing Rd., Chutung, Hsinchu 310, Taiwan

**Department of Computer Science and Information Engineering, Chung-Hua University, 707, Sec. 2, WuFu Rd., Hsinchu 30012, Taiwan

***Department of Micro-Nano Systems Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan

August 28, 2011
March 7, 2012
February 20, 2013
autonomous mobile robot, composite map construction, visual localization, feature point extraction, feature point matching
In this paper, we propose a novel mobile robot visual localization method consisting of two processing stages: map construction and visual localization. In the map construction stage, both laser range finder and camera are used to construct a composite map. Depth data are collected from laser range finder while distinct features of salient feature points are gathered from camera provided images. In the visual localization stage, only camera is used and the robot system detects feature points from camera provided images, computes features of the detected feature points, matches them with the features recorded in previously constructed composite map, and decides location of the robot. Using this method, a robot can locate its own position effectively without expensive laser range finder so that greater acceptance can be expected due to affordability. With the proposedmethod, several experiments have been performed. The matching accuracy of proposed feature extraction achieves 97.79%, compared with 92.96% of SURF. Experiment results show that our method not only reduces hardware cost of robot localization, but also offers high accuracy.
Cite this article as:
H. Yu, H. Hsieh, Y. Tasi, Z. Ou, Y. Huang, and T. Fukuda, “Visual Localization for Mobile Robots Based on Composite Map,” J. Robot. Mechatron., Vol.25 No.1, pp. 25-37, 2013.
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Last updated on Jun. 03, 2024