自主移动机器人定位系统中Kalman滤波算法改进*

为了解决常规Kalman滤波算法在移动机器人定位过程中运算量大、精度不高的问题，在分析传统Kalman滤波器缺点的基础上，提出了一种基于UT参数变换的方法对常规Kalman滤波算法进行了改进。改进后的Kalman滤波算法消减了传统Kalman滤波器高阶项无法忽略而带来的误差。实验结果表明，改进型的Kalman滤波算法使机器人的最大位置偏差得到减小，对移动机器人的定位精度有明显改善，误差仿真曲线表明，改进后的定位结果误差波动不明显，使定位系统的稳定性得到了较大提高。

Improved Kalman filter algorithm in positioning system for autonomous mobile robot

In order to solve the problem that the large amount of computation and low accuracy of kalman filtering algorithm to the conventional mobile robot localization process, according to the analysis of the traditional kalman filter,the article gived a method of improving the conventional kalman filter by U-T parameter transformation, the improved kalman filtering algorithm reduced the error that brought by the traditional kalman filter which can not ignore the high-end items.The experimental results show that the maximum position deviation was reduced by the improved kalman filtering algorithm.The accuracy of the mobile robot positioning has been significantly improved. Error Simulation curve shows the results of the improved positioning error deviation is not obvious, the stability of the positioning system has been greatly improved.