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

doi:10.13973/j.cnki.robot.2017.0205

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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. ROBOT, 2017, 39(2): 205-213. DOI: 10.13973/j.cnki.robot.2017.0205.

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．

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	达兴鹏
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	王雯珊

关键词 ：差速移动, 移动机器人, 里程计标定, 激光雷达位姿标定, 扩展卡尔曼滤波

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.

Key words： differential drive mobile robot odometry calibration laser rangefinder pose calibration extended Kalman filter

收稿日期: 2016-11-28 录用日期: 2017-01-22

TP242.6

基金资助:国家自然科学基金（61673261）；教育部博士点基金（20090073110037）；教育部重大项目培育资金（708035）；上海市教委创新项目（12ZZ014）；国家863计划（2012AA10A506）

通讯作者: 曹其新,qxcao@sjtu.edu.cn E-mail: qxcao@sjtu.edu.cn

作者简介: 达兴鹏(1992-),男,硕士生.研究领域:移动机器人误差标定,移动机械臂抓取.
曹其新(1960-),男,博士,教授,博士生导师.研究领域:泛在机器人技术,机器人组件化与中间件技术,机器视觉与模式识别,移动机械臂技术等.
王雯珊(1986-),女,博士生.研究领域:泛在机器人技术,任务规划.

链接本文:

https://robot.sia.cn/CN/10.13973/j.cnki.robot.2017.0205 或 https://robot.sia.cn/CN/Y2017/V39/I2/205

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