所属单位：电气与电子工程学院
发表刊物：IFAC-PapersOnLine
项目来源：省、市、自治区科技项目
关键字：Visual servoingImage Jacobian matrixKalman filterMaximum correntropy criterionnon-Gaussian noise
摘要：A major challenge in solving robot visual servoing problems with unstructured environments is to obtain image Jacobian matrix, especially non-Gaussian noise always exist in the whole process. However, the standard Kalman Filter (KF) is exhausted to find the optimal value under Gaussian noise assumption. In this paper, a Kalman filter which adopted the maximum correntropy criterion (MCC) instead of the minimum mean square error (MMSE) criterion is proposed to solve the approximation issue of the image Jacobian. The simulation and experiment results using a conventional 6R manipulator are conducted to verify the effectiveness of the proposed method.
合写作者：李洪文,任晓琳
第一作者：任晓琳
论文类型：论文集
页面范围：1
是否译文：否
发表时间：2020-12-03