摘要
研究UHF-RFID环境中移动机器人的定位问题,提出一种基于自适应UKF滤波器组的移动机器人定位方法,融合UHF-RFID和机器人内部传感器信息,以实现初始位姿未知的移动机器人定位.首先,利用UHF-RFID系统对移动机器人进行初始定位,并根据其初始位置信息随机生成移动机器人的初始状态估计集;然后,考虑UHFRFID系统定位的量化误差,应用自适应UKF方法对机器人的状态估计集进行预测和更新,并对状态估计集进行有效地裁剪、筛选以及更新,以提高滤波器的估计精度和稳定性.仿真结果表明,相比于标准UKF滤波方法,自适应UKF滤波器组方法具有更高的定位精度和更快的收敛速度.
This paper investigates the problem of mobile robot localization in ultra high frequency-radio frequency identification（UHF-RFID）, and a localization method of the mobile robot is presented based on an adaptive UKF bank to integrate the information of UHF-RFID and odometer for the mobile robot localization with an unknown initial pose.Firstly, by using the UHF-RFID, the initial estimate of the position of the mobile robot is obtained, and a set of estimates can be generated randomly according to the initial estimate. Then, taking the quantization error into consideration, an adaptive UKF is applied to update the estimate set, and accordingly, the estimate set is pruned and updated, which helps to improve the accuracy and stability of the filter. The results of the simulation show that the adaptive UKF bank has higher accuracy and faster convergence compared with the standard UKF.
作者
张文安
陈国庆
杨旭升
ZHANG Wen-an;CHEN Guo-qing;YANG Xu-sheng(College of Information Engineering,Zhejiang University of Technology,Hangzhou 310023,China;Key Laboratory of System Control and Information Processing of Ministry of Education,Shanghai 200240,China)
出处
《控制与决策》
EI
CSCD
北大核心
2018年第10期1807-1812,共6页
Control and Decision
基金
国家自然科学基金项目(61573319)
浙江省杰出青年科学基金项目(LR16F030005)
系统控制与信息处理教育部重点实验室项目
