Real-time Apriltag Inertial Fusion Localization for Large Indoor Navigation

被引：2
作者：
Chen, Jianwei [1 ]
Gao, Yue [2 ]
Li, Shaoyuan [1 ]
机构：
[1] Shanghai Jiao Tong Univ, Dept Automat, Shanghai, Peoples R China
[2] Shanghai Jiao Tong Univ, Dept Automat, MoE Key Lab Artificial Intelligence, Shanghai, Peoples R China
来源：
2020 CHINESE AUTOMATION CONGRESS (CAC 2020) | 2020年
基金：
中国国家自然科学基金;
关键词：
Apriltag; Indoor Localization; Data Fusion; IEKF; ROBUST;
D O I：
10.1109/CAC51589.2020.9326501
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Localization in large indoor environment is a challenging problem due to lighting variation and dynamic objects. In this paper, we propose a method for indoor navigation utilizing motion data and Apriltag. The advantage of Apriltag is its invariance to uncertainty in the environment. However, due to the need to minimize the number of Apriltags installed, motion data are required. Hence, in this work, iterative extended Kalman filter(IEKF) method is utilized to fuse visual information and motion data. Furthermore, area detection algorithm is proposed to speed up Apriltag processing speed. In the experiment section, we compared our methods with OpenVSLAM and ground truth Lidar trajectory. In addition, we compared each frame processing time with and without the Apriltag fast detection algorithm.
引用
收藏
页码：6912 / 6916
页数：5
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