renxiaolin
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- Name (Pinyin):renxiaolin
- Date of Birth:1985-08-13
- E-Mail:
- Teacher College:电气与电子工程学院
Contact Information
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- Paper Publications
Online Image Jacobian Identification Using Optimal Adaptive Robust Kalman Filter for Uncalibrated Visual Servoing
Release time:2022-12-12 Hits:
- Affiliation of Author(s):电气与电子工程学院
- Journal:2017 2ND ASIA-PACIFIC CONFERENCE ON INTELLIGENT ROBOT SYSTEMS (ACIRS）
- Funded by:省、市、自治区科技项目
- Key Words:servoing; image Jacobian identification; adaptive Kalman filter; adaptive factor
- Abstract:Dynamic image Jacobian matrix identification is proved complicated and tough in uncalibrated visual servoing. Comparing with standard Kalman Filter (KF), which is exhausted to find the optimal value of unknown noise covariance, the adaptive robust KF is developed to deal with uncertainty noise covariance information. The state model and measurement of noise covariance matrices are adopted recursive estimation to tune unknown variation respectively, and an adaptive factor is employed to adjust the estimated state vector by using residual sequence. The simulation results show that the proposed algorithm has better performance for using a robotic manipulator with eye-in-hand configuration when the noise variances statistical information of the system is indeterminate.
- Co-author:李洪文,liyuanchun,任晓琳
- First Author:renxiaolin
- Indexed by:Essay collection
- Page Number:2
- Translation or Not:no
- Date of Publication:2017-06-16