%0 Journal Article
%T Simultaneous Localization and Mapping System Based on Labels<br>Simultaneous Localization and Mapping System Based on Labels
%A Tong Liu
%A Panpan Liu
%A Songtian Shang
%A Yi Yang
%J 北京理工大学学报（自然科学中文版)
%D 2017
%R 10.15918/j.jbit1004-0579.201726.0413
%X In this paper a label-based simultaneous localization and mapping (SLAM) system is proposed to provide localization to indoor autonomous robots. In the system quick response(QR) codes encoded with serial numbers are utilized as labels. These labels are captured by two webcams, then the distances and angles between the labels and webcams are computed. Motion estimated from the two rear wheel encoders is adjusted by observing QR codes. Our system uses the extended Kalman filter (EKF) for the back-end state estimation. The number of deployed labels controls the state estimation dimension. The label-based EKF-SLAM system eliminates complicated processes, such as data association and loop closure detection in traditional feature-based visual SLAM systems. Our experiments include software-simulation and robot-platform test in a real environment. Results demonstrate that the system has the capability of correcting accumulated errors of dead reckoning and therefore has the advantage of superior precision.<br>In this paper a label-based simultaneous localization and mapping (SLAM) system is proposed to provide localization to indoor autonomous robots. In the system quick response(QR) codes encoded with serial numbers are utilized as labels. These labels are captured by two webcams, then the distances and angles between the labels and webcams are computed. Motion estimated from the two rear wheel encoders is adjusted by observing QR codes. Our system uses the extended Kalman filter (EKF) for the back-end state estimation. The number of deployed labels controls the state estimation dimension. The label-based EKF-SLAM system eliminates complicated processes, such as data association and loop closure detection in traditional feature-based visual SLAM systems. Our experiments include software-simulation and robot-platform test in a real environment. Results demonstrate that the system has the capability of correcting accumulated errors of dead reckoning and therefore has the advantage of superior precision.
%K simultaneous localization and mapping (SLAM) extended Kalman filter (EKF) quick response(QR) codes artificial landmarks&lt
%K br&gt
%K simultaneous localization and mapping (SLAM) extended Kalman filter (EKF) quick response(QR) codes artificial landmarks
%U http://journal.bit.edu.cn/yw/bjlgyw/ch/reader/view_abstract.aspx?file_no=20170413&flag=1