机器人多维力传感器标定Kalman滤波

	机器人多维力传感器标定Kalman滤波
其他题名	Kniman Filter for the Multi-Component Force/Moment Sensor of Robot Calibration
	许德章; 葛运建; 高理富
	2006
发表期刊	电子测量与仪器学报
ISSN	1000-7105
摘要	在多维力传感器标定过程中，往往出现比较大测量噪声，零漂幅度较大，严重地限制了多维力传感器标定精度。鉴于Kalman滤波器在滤除系统随机干扰噪声方面良好效果，并考虑到在力传感器标定加载前，噪声信号便于测量的特点。本文从单维力传感器入手，把标定测量模型简化为一阶惯性和零阶保持器串联，并把传感器的输入／输出分为有载荷作用和无载荷作用两个状态，分别推导出输入／输出关系，获得单维力传感器状态和测量方程，并进一步推导出单维力传感器Kalman滤波算法。在合理假设基础上，再使单维力传感器标定Kalman滤波算法推广到多维力传感器。标定实验表明，在多维力传感器标定中，Kalman滤波有效地滤除了测量噪声，提高了标定精度。
合作性质	其它
其他摘要	During calibrating for multi-component force/moment sensors, there are often measure noises that exhibit more draft range. Because it is difficult to cancel the drifts by analog circuit filters, the drifts badly restrict calibration precision of multi-component force/moment sensor. According to Kalman filtering fine effect of canceling drift, and convenience for measuring easily noise signals of the multi-component force/moment sensor, the paper simplified the single-component force sensor into a system for a series connection with a class inertial device and zero-holder. After the input and output of the single-component force sensor is divided into two states with load and without load, then the input and output relation of the single-component force sensor is derived respectively, finally the state and measure equations are inferred. Based on reasonable hypothesis, Kalman filtering for single-component force sensor is applied to the multi-component sensor. The Calibration experiment showed that filtering algorithm is successful in canceling drift, and improving effectively the calibrating precision of multi-component force/moment sensor.
关键词	多维力传感器机器人标定 Kalman 滤波
学科领域	仿生感知技术
收录类别	其他
语种	中文
CSCD记录号	CSCD:2330606
文献类型	期刊论文
条目标识符	http://ir.hfcas.ac.cn:8080/handle/334002/916
专题	中科院合肥智能机械研究所
推荐引用方式 GB/T 7714	许德章,葛运建,高理富. 机器人多维力传感器标定Kalman滤波[J]. 电子测量与仪器学报,2006,20(1).
APA	许德章,葛运建,&高理富.(2006).机器人多维力传感器标定Kalman滤波.电子测量与仪器学报,20(1).
MLA	许德章,et al."机器人多维力传感器标定Kalman滤波".电子测量与仪器学报 20.1(2006).

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