@inproceedings{1232b78d6a024d49b00f9f9a3d43b0a7,
title = "Laser sensor based localization of mobile robot using Unscented Kalman Filter",
abstract = "The objective is to determine mobile robots position and orientation by integrating information received from laser distance sensor and encoders. The robot is maneuvered in a known environment, and the laser ranging finder can get information of geometrical primitives like lines and polygons to extract landmarks of the environment. With the off-line map, the position and orientation of the robot can be estimated. To improve the precision of our localization system, we present a sensor-data-fusion method using Unscented Kalman Filter (UKF).",
keywords = "Localization, Mobile robot, Unscented Kalman Filter",
author = "Qiang Xu and Chang Ren and Haoyue Yan and Junhong Ji",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 13th IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2016 ; Conference date: 07-08-2016 Through 10-08-2016",
year = "2016",
month = sep,
day = "1",
doi = "10.1109/ICMA.2016.7558824",
language = "英语",
series = "2016 IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1726--1731",
booktitle = "2016 IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2016",
address = "美国",
}