测试技术学报2018，Vol.32Issue(4)：292-299,8.DOI:10.3969/j.issn.1671-7449.2018.04.003
基于改进扩展卡尔曼滤波算法的移动机器人定位方法研究
Research on Positioning Method of Mobile Robot Based on Improved Extended Kalman Filtering Algorithm
摘要
Abstract
Aiming at the problem that single sensor or multi-sensor measurement system has limited a-bility to process environmental information in the process of position and orientation tracking of mobile robots,the author made the fusion analysis on the measurement information combine with the extended Kalman filter algorithm.For n observations measured by a single sensor,the author extended the obser-vation matrix to m target measurements and designed the mapping from the prediction space to the meas-urement space to a transformation matrix which has n non-zero variables,nm dimension and rank n to a-chieve local updating of the state vector by the sensor.Experiments were taken on the ground mobile ro-bot based on the established sensors and robot motion mathematical model.Theoretical analysis and ex-perimental results show that the proposed method improves the generalization ability of the algorithm for different types and numbers of sensors under the premise of ensuring the positioning accuracy ,mean-while,enhance the accuracy and flexibility of the measurement system.关键词
移动机器人/扩展卡尔曼滤波/多传感器融合Key words
mobile robot/extended Kalman filter/multi-sensor fusion分类
信息技术与安全科学引用本文复制引用
陈庆武,张志安,何雨,韩明明,黄学功..基于改进扩展卡尔曼滤波算法的移动机器人定位方法研究[J].测试技术学报,2018,32(4):292-299,8.基金项目
国家自然科学基金资助项目(11772160) （11772160）
