Abstract: For the difficult problem of mobile robot positioning in indoor environment, this paper puts forward the Kalman filter positioning algorithm based on RSSI. The positioning algorithm based on RSSI is utilized to forecast the location of user, which the Kalman filter is used to optimize, in order to enhance the performance and stability of indoor positioning system. Experimental results show that the Kalman filter positioning algorithm, which has the robustness, can effectively improve the locational precision of indoor positioning system, and that the prospective objective is reached.

Key words: robot positioning, indoor environment, least squares method, Kalman filter

摘要： 针对移动机器人在室内环境中定位难的问题，提出了一种基于RSSI（Receive Signal Strength Indicator）的卡尔曼滤波定位算法。利用基于RSSI的定位方法估算用户的位置坐标，利用卡尔曼滤波算法对用户的估算位置坐标进行优化处理，以提高室内定位系统的性能和稳定性。实验结果表明，卡尔曼滤波算法是鲁棒的，可以有效改善系统的定位精度，达到了预期的目的。

关键词: 机器人定位, 室内环境, 最小二乘法, 卡尔曼滤波