机器人2011，Vol.33Issue(5)：621-627,7.DOI:10.3724/SP.J.1218.2011.00621
基于无迹卡尔曼滤波的机器人手眼标定
Robot Hand-Eye Calibration Using Unscented Kalman Filtering
摘要
Abstract
An online robot hand-eye calibration method using unscented Kalman filtering (UKF) is presented to solve the homogeneous transformation equations of the form AX = XB. The hidden Markov model (HMM) of the hand-eye calibration is constructed, based on which UKF is performed to estimate calibration parameters recursively according to the Bayesian theory, and the evolution of calibration parameters can be visualized in real time. Monte Carlo simulation shows that the proposed algorithm possesses better accuracy than the traditional least squares (LS) based method under low isotropic, high isotropic and anisotropic Gaussian noises. Real robot hand-eye calibration experiment is also performed and the result shows stable convergence of the proposed algorithm with better accuracy comparing with the LS based method.关键词
手眼标定/隐式马尔可夫模型/贝叶斯估计/无迹卡尔曼滤波Key words
hand-eye calibration/ hidden Markov model/ Bayesian estimation/ unscented Kalman filtering (UKF)分类
信息技术与安全科学引用本文复制引用
王君臣,王田苗,杨艳,胡磊..基于无迹卡尔曼滤波的机器人手眼标定[J].机器人,2011,33(5):621-627,7.基金项目
国家863计划资助项目(2008AA040205) （2008AA040205）
国家科技支撑计划资助项目(2011BAF01B02). （2011BAF01B02）
