@inproceedings{99f3a90351d4451b86b6907d4372bbcc,
title = "A self-correcting localization approach for automobile robots based on the two dimensional LADAR",
abstract = "In this paper, a novel localization approach for autonomous mobile robots is proposed. It can accomplish the all-terrain localization function with the laser radar (LADAR) and the inertial measurement unit (IMU). First of all, for the multiple-input nonlinear localization system, a fuzzy filter is built up to estimate the position of the mobile robot. Then, an efficient evaluation index is raised to determine whether the landmarks extracted from the adjacent data frame are the same, which can help the mobile robot to realize the self-correction function. In the final, the experiments in the real world are implemented to show the effectiveness of the proposed approach.",
keywords = "Fuzzy filter, Localization, Obstacle match, SLAM, Self-correcting",
author = "Jing Li and Wenxue Liu and Junzheng Wang and Jianan Qiao",
note = "Publisher Copyright: {\textcopyright} 2016 TCCT.; 35th Chinese Control Conference, CCC 2016 ; Conference date: 27-07-2016 Through 29-07-2016",
year = "2016",
month = aug,
day = "26",
doi = "10.1109/ChiCC.2016.7554339",
language = "English",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "6261--6265",
editor = "Jie Chen and Qianchuan Zhao and Jie Chen",
booktitle = "Proceedings of the 35th Chinese Control Conference, CCC 2016",
address = "United States",
}