摘要
为了提高自主导航机器人的室内定位精度,提出一种基于粒子滤波的超带宽(UWB)/惯导融合定位算法。首先,UWB定位采用双边双向测距算法确定距离信息,通过三边定位算法确定位置信息。其次,惯导定位通过编码器采集运动信息,建立非完整约束下的动力学模型,确定运动轨迹。两种定位信息在上位机中通过粒子滤波进行融合,实现高精度融合定位。仿真结果表明,与单一UWB定位相比,基于粒子滤波的融合定位算法定位误差降低了66.41%。
In order to improve the indoor positioning accuracy of automatic guided robot,a fusion positioning algorithm of UWB and inertial navigation based on particle filter is proposed.Firstly,the UWB adopts the double-sided two-way-ranging algorithm to get the information of distance,and adopts the trilateration to get the information of location.Secondly,the inertial navigation collects motion information through the encoder,establishes the kinematic model under nonholonomic constraints,and gets the trajectory.The two kinds of positioning information are fused by particle filter in the upper computer to achieve high precision fusion positioning.The simulation results show that compared with the single UWB,the positioning error of the fusion positioning algorithm based on particle filter is reduced by 66.41%.
作者
鞠昆廷
万熠
梁西昌
侯嘉瑞
周有杰
Ju Kunting;Wan Yi;Liang Xichang;Hou Jiarui;Zhou Youjie(School of Mechanical Engineering,Shandong University,Jinan 250061,China)
出处
《单片机与嵌入式系统应用》
2021年第4期30-33,共4页
Microcontrollers & Embedded Systems
基金
山东省重点研发计划—面向开阔环境巡检的智能安防机器人关键技术研究及应用示范(2019JZZY010112)
山东大学教育教学改革研究项目(2020Y211)。
关键词
室内定位
超带宽
粒子滤波
惯导
indoor positioning
ultra-wide band
particle filter
inertial navigation
