基于激光跟踪测量的机器人定位研究
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摘要
机器人定位具有较高的实际应用价值,成为当前关注的热点,为了解决当前机器人定位算法存在的定位效率低、定位误差大等难题,以提高机器人定位精度为目标,设计了一种基于激光跟踪测量的机器人定位算法。首先对机器人定位原理进行分析,找到影响机器人定位精度的因素,然后采用激光传感器对机器人移动状态进行采集,并采用主成分分析法对原始机器人信息进行处理,降低机器人信息的冗余度,最后采用粒子滤波算法对机器人进行定位,并进行了机器人定位仿真实验。结果表明,本文算法可以快速、高精度实现机器人定位,无论是定位精度或者定位实时性,均要明显优化对比机器人定位算法,具有更高的实际应用价值。
Robot positioning has a high practical application value. It has become a hot spot of attention. In order to solve the problem of location efficiency and location error in the current robot positioning algorithm,to improve the positioning accuracy of robot,a robot positioning algorithm based on laser tracking measurement is designed. Firstly,the principle of robot positioning is analyzed,and the factors that affect the positioning accuracy of the robot are found.Then the laser sensor is used to collect the dynamic state of the robot,and the principal component analysis of the information of the original robot is used to reduce the redundancy of the robot information. The robot is positioned by the least particle filter algorithm. And the simulation experiment of robot positioning is carried out. The results show that the algorithm can achieve fast and accurate positioning of the robot. Both the positioning accuracy and the real-time positioning of the robot should be significantly optimized.
Robot positioning has a high practical application value. It has become a hot spot of attention. In order to solve the problem of location efficiency and location error in the current robot positioning algorithm,to improve the positioning accuracy of robot,a robot positioning algorithm based on laser tracking measurement is designed. Firstly,the principle of robot positioning is analyzed,and the factors that affect the positioning accuracy of the robot are found.Then the laser sensor is used to collect the dynamic state of the robot,and the principal component analysis of the information of the original robot is used to reduce the redundancy of the robot information. The robot is positioned by the least particle filter algorithm. And the simulation experiment of robot positioning is carried out. The results show that the algorithm can achieve fast and accurate positioning of the robot. Both the positioning accuracy and the real-time positioning of the robot should be significantly optimized.
引文
[1]郑帅超,房立金,徐志刚.单目视觉-激光测距定位系统的标定与姿态校正[J].机械科学与技术,2017,36(12):1926-1934.
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[12]王元华,李贻斌,汤晓.基于激光雷达的移动机器人定位和地图创建[J].微计算机信息,2009,25(14):227-229.
[13]刘丽雯,张崇巍,徐玉华,汪木兰.基于UKF的室内移动机器人定位问题[J].合肥工业大学学报(自然科学版),2009,32(1):9-13.
[14]赵璇,何波,吉德志,等.基于粒子滤波的机器人定位及动态目标跟踪[J].系统仿真学报,2008,20(23):6490-6493,6497.
[15]钱,马旭东,戴先中,房芳.同时机器人定位与人体跟踪的多源感知协作粒子滤波方法[J].机器人,2008,30(6):491-497.
[16]孙自飞,马旭东,戴先中.多传感器的移动机器人可定位性估计与自定位[J].智能系统学报,2017,12(4):443-449.
[2]何晓煦,田威,曾远帆,等.面向飞机装配的机器人定位误差和残差补偿[J].航空学报,2017,38(4):292-302.
[3]何庆稀,游震洲,孔向东.一种基于位姿反馈的工业机器人定位补偿方法[J].中国机械工程,2016,27(7):872-876.
[4]梁爽,曹其新,王雯珊,邹风山.基于强化学习的多定位组件自动选择方法[J].智能系统学报,2016,11(2):149-154.
[5]钱晓明,张浩,王晓勇,武星.基于激光扫描匹配的移动机器人相对定位技术研究[J].农业机械学报,2016,47(3):14-21.
[6]许亚芳,孙作雷,曾连荪,张波.基于激光扫描和迭代贝叶斯策略的定位[J].计算机工程与设计,2015,36(12):3333-3338.
[7]王勇,陈卫东,王景川,肖鹏.面向动态高遮挡环境的移动机器人自适应位姿跟踪算法[J].机器人,2015,37(1):112-121.
[8]韩同辉,沈超,沈静,顿向明.基于PF算法的移动机器人定位研究[J].机电一体化,2012,18(3):13-16,96.
[9]刘焕玲,刘桂华,刘钦.基于一维激光测距仪的室内移动机器人定位[J].工具技术,2011,45(10):79-83.
[10]唐骥锋,刘国栋.多传感器融合改进的机器人定位决策[J].计算机系统应用,2011,20(10):120-124.
[11]谭永丽,方彦军,俞进萍.基于Matlab的有路标移动机器人定位仿真[J].武汉大学学报(工学版),2010,43(6):784-787,791.
[12]王元华,李贻斌,汤晓.基于激光雷达的移动机器人定位和地图创建[J].微计算机信息,2009,25(14):227-229.
[13]刘丽雯,张崇巍,徐玉华,汪木兰.基于UKF的室内移动机器人定位问题[J].合肥工业大学学报(自然科学版),2009,32(1):9-13.
[14]赵璇,何波,吉德志,等.基于粒子滤波的机器人定位及动态目标跟踪[J].系统仿真学报,2008,20(23):6490-6493,6497.
[15]钱,马旭东,戴先中,房芳.同时机器人定位与人体跟踪的多源感知协作粒子滤波方法[J].机器人,2008,30(6):491-497.
[16]孙自飞,马旭东,戴先中.多传感器的移动机器人可定位性估计与自定位[J].智能系统学报,2017,12(4):443-449.