达兴鹏, 曹其新, 王雯珊. 移动机器人里程计系统误差及激光雷达安装误差在线标定[J]. 机器人, 2017, 39(2): 205-213. DOI: 10.13973/j.cnki.robot.2017.0205
引用本文: 达兴鹏, 曹其新, 王雯珊. 移动机器人里程计系统误差及激光雷达安装误差在线标定[J]. 机器人, 2017, 39(2): 205-213. DOI: 10.13973/j.cnki.robot.2017.0205
DA Xingpeng, CAO Qixin, WANG Wenshan. On-line Calibration for Odometry Systematic Errors and Laser Rangefinder Installation Errors of a Mobile Robot[J]. ROBOT, 2017, 39(2): 205-213. DOI: 10.13973/j.cnki.robot.2017.0205
Citation: DA Xingpeng, CAO Qixin, WANG Wenshan. On-line Calibration for Odometry Systematic Errors and Laser Rangefinder Installation Errors of a Mobile Robot[J]. ROBOT, 2017, 39(2): 205-213. DOI: 10.13973/j.cnki.robot.2017.0205

移动机器人里程计系统误差及激光雷达安装误差在线标定

On-line Calibration for Odometry Systematic Errors and Laser Rangefinder Installation Errors of a Mobile Robot

  • 摘要: 为了降低传感器系统误差所带来的影响,首先建立了差速移动机器人里程计系统误差及激光雷达安装误差数学模型.然后,基于拓展卡尔曼滤波算法,提出了一种里程计系统误差及激光雷达安装误差迭代标定方法,该方法能够在定位的同时对2组误差进行实时标定.通过仿真对该方法进行验证,误差估计有效地收敛到误差真值.实物实验中,误差估计能有效收敛,标定后的航迹推算误差大幅度降低.

     

    Abstract: In order to reduce the influence of sensor systematic errors, a mathematical model of odometry systematic error and laser rangefinder installation error of differential-drive mobile robot is established firstly. Then, an iterative calibration method based on extended Kalman filter algorithm is proposed for odometry systematic error calibration and laser rangefinder installation error calibration, which can calibrate these two sets of errors during localization in real time. When verifying the method by simulation, the errors estimation can effectively converge to the true values of the errors. While in physical experiments, the errors estimation can effectively converge, and the error of dead-reckoning is greatly reduced after calibration.

     

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