计算机与数字工程2017，Vol.45Issue(8)：1482-1484,1527,4.DOI:10.3969/j.issn.1672-9722.2017.08.005
基于EKF和UKF的移动机器人定位算法优化与仿真
Optimization and Simulation of Mobile Robot Localization Algorithm Based on EKF and UKF
摘要
Abstract
In order to study the location prediction effect of Kalman filter algorithm in nonlinear system,the application re-sults of the extended Kalman filter algorithm and the unscented Kalman filter algorithm are analyzed and compared and according to the force condition of the mobile robot,the modificatory factor is introduced into the localization algorithm to improve the state esti-mation equation. The simulation results show that the location prediction effect of the unscented Kalman filter algorithm is better than that of extended Calman filter algorithm in nonlinear system and the modificatory factor produces an improvement effect on both algorithms.关键词
移动机器人/扩展卡尔曼滤波/无迹卡尔曼滤波/定位算法改进/位置预测仿真Key words
mobile robot/extended Kalman filtering/unscented Kalman filter/localization algorithm improvement/loca-tion prediction simulation分类
信息技术与安全科学引用本文复制引用
靳果,袁铸..基于EKF和UKF的移动机器人定位算法优化与仿真[J].计算机与数字工程,2017,45(8):1482-1484,1527,4.基金项目
国家自然科学基金项目(编号:71501153) （编号:71501153）
河南省基础与前沿技术研究计划(自然科学基金)(编号:122300410416)资助. （自然科学基金）
