Uncalibrated Image-Based Visual Servoing Control with Maximum Correntropy Kalman Filter
نویسندگان
چکیده
منابع مشابه
Maximum Correntropy Kalman Filter
—Traditional Kalman filter (KF) is derived under the well-known minimum mean square error (MMSE) criterion, which is optimal under Gaussian assumption. However, when the signals are non-Gaussian, especially when the system is disturbed by some heavy-tailed impulsive noises, the performance of KF will deteriorate seriously. To improve the robustness of KF against impulsive noises, we propose in ...
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A new algorithm called maximum correntropy unscented Kalman filter (MCUKF) is proposed and applied to relative state estimation in space communication networks. As is well known, the unscented Kalman filter (UKF) provides an efficient tool to solve the non-linear state estimate problem. However, the UKF usually plays well in Gaussian noises. Its performance may deteriorate substantially in the ...
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We propose a method for visual control of a robotic system which does not require the formulation of an explicit calibration between image space and the world coordinate system. Calibration is known to be a difficult and error prone process. By extracting control information directly from the image, we free our technique from the errors normally associated with a fixed calibration. We demonstra...
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Visual servoing is a process to enable a robot to position a camera with respect to known landmarks using the visual data obtained by the camera itself to guide camera motion. A solution is described which requires very little a priori information freeing it from being speciic to a particular connguration of robot and camera. The solution is based on closed loop control together with deliberate...
متن کاملMaximum correntropy unscented filter
Xi Liu, Badong Chena∗, Bin Xu, Zongze Wu, and Paul Honeine School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an, China; School of Automation, Northwestern Polytechnical University, Xi’an, China; School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China; the Normandie Univ, UNIROUEN, UNIHAVRE, INSA Rouen, LITIS, Rouen, ...
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ژورنال
عنوان ژورنال: IFAC-PapersOnLine
سال: 2020
ISSN: 2405-8963
DOI: 10.1016/j.ifacol.2021.04.200