一种新的基于RFID的室内移动机器人自定位方法研究

针对室内移动机器人自定位算法定位精度不高、定位误差存在波动的问题，提出了一种RTFL(RFID tag floor based localization)定位算法与RSSI定位算法相结合的室内移动机器人自定位方法。由RTFL定位算法给定机器人位置估算初值和机器人所在的范围，然后通过基于RSSI的机器人自定位系统进行机器人位置的进一步精确定位。求解过程中，通过遗传算法求解极大似然方程组，并且提出了染色体的筛选和剔除策略。仿真实验结果表明：该方法在有效的时间内完成定位，平均定位误差为0.1572m，与传统的改进方法0.33214m的定位误差相比，降低了近一倍。并且新方法受环境影响较小，鲁棒性较好，能够很好的满足室内移动机器人的定位要求。

Research on A Novel Self-Localization Method for Indoor Robot Based on RFID

Aiming at the fact that the low positioning accuracy and the large fluctuation of the current self-Localization algorithm for indoor mobile robot. An algorithm using RTFL (RFID tag floor based localization) and RSSI positioning method was proposed. The new method was less affected by the environment and had higher localization accuracy. The initial estimation position of the robot and the boundary of the robot may exist were given by RTFL algorithm, which could shorten the search range and reduce the computational time of genetic algorithm effectively. A method that solves the maximum likelihood equations by the genetic algorithm was also proposed, in which strategy of chromosomes selecting and deleting was adopted. The results of experiments show that the new system is less affected by environment, has a good robustness and can accomplish positioning effectively. Positioning accuracy of the new system can reach 0.1572m, increasing by one time than traditional error 0.33214m, and it can well meet the requirement of indoor mobile robot localization.