Localization of mobile robot based on multi-sensor fusion

被引：0
|
作者：
Gao, Yu [1 ]
Wang, Fei [2 ]
Li, Jinghong [1 ]
Liu, Yuqiang [2 ]
机构：
[1] Northeast Univ, Coll Informat Sci & Engn, Shenyang 110819, Peoples R China
[2] Northeast Univ, Fac Robot Sci & Engn, Shenyang 110169, Peoples R China
来源：
PROCEEDINGS OF THE 32ND 2020 CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2020) | 2020年
关键词：
Mobile robot; Localization; Extended Kalman filter; Multiple-sensors fusion;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In order to realize the precise positioning of mobile robot, the data information of multiple sensors needs to be collected by the localization system to enhance the state estimation ability of robot. Due to the need for accurate calibration and initialization of sensor groups, as well as the processing of measurement errors with different rates and delays, multi-sensor fusion still needs to solve many problems and faces many challenges. A method of multi-sensor fusion, which can analyze and screen the signal quality of sensors is proposed in this paper. Based on the extended Kalman filter, UWB data, IMU data and Lidar data are fused. By filtering and processing the sensor information, the impact of noise can be reduced. At the same time, the results of various sensor information fusion are closer to the actual results, and the mobile robot can be located.
引用
收藏
页码：4367 / 4372
页数：6
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