新的室内移动机器人自定位方法  

New self-localization method for indoor mobile robot

作　　者：周艳聪[1] 董永峰[2] 王安娜[2] 顾军华[2] 

机构地区：[1]天津商业大学信息工程学院,天津300134 [2]河北工业大学计算机科学与软件学院,天津300401

出　　处：《计算机应用》2015年第2期585-589,594,共6页journal of Computer Applications

基　　金：天津市自然科学基金面上项目(14JCYBJC15900);天津市自然科学基金重点项目(12JCZDJC21200)

摘　　要：针对现有室内移动机器人自定位方法中存在的定位精度不高,随时间积累定位误差增大,复杂室内环境下信号存在多径效应和非视距效应等问题,提出了一种基于蒙特卡罗定位(MCL)的新的移动机器人自定位方法。首先,通过分析基于无线射频识别(RFID)技术的移动机器人自定位系统,建立机器人运动模型;然后,通过分析基于接收信号强度指示(RSSI)的移动机器人自定位系统,提出机器人移动过程的观测模型;最后,针对粒子滤波定位执行效率不高的问题,提出粒子剔除策略和依据粒子方位赋予粒子权值策略,提高系统的定位精度和执行效率。仿真实验表明,机器人在移动过程中的自定位误差在X轴和Y轴方向上为3 cm,传统定位算法误差为6 cm,新算法定位精度提高近1倍,且算法具有很好的鲁棒性。Aiming at the problems of the current self-localization algorithms for indoor mobile robot, such as the low positioning accuracy, increasing positioning error with time, the signal＇s muhipath effect and non-line-of-sight effect, a new mobile robot self-localization method based on Monte Carlo Localization （MCL） was proposed. Firstly, through analyzing the mobile robot self-localization system based on Radio Frequency IDentification （RFID）, the robot motion model was established. Secondly, through the analysis of the mobile robot positioning system based on Received Signal Strength Indicator （RSSI）, the observation model was put forward. Finally, in order to improve the computing efficiency of particle filter, the particle culling strategy and particle weight strategy considering orientation of the particles were given, to enhance the positioning accuracy and the execution efficiency of the new positioning system. The position errors of the new algorithm were about 3 cm in both the X direction and the Y direction, while position error of the traditional localization algorithm in the X direction and the Y direction were both about 6 cm. Simulation results show that the new algorithm doubles the positioning accuracy, and has good robustness.

关 键 词：机器人自定位 射频识别 极大似然定位方法 蒙特卡罗定位 粒子滤波 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术] TP18[自动化与计算机技术—计算机科学与技术]