An Extended Kalman Filter for Real-Time Estimation and Control of a Rigid-Link Flexible-Joint Manipulator
The project of Random Signals, Adaptive, and Kalman Filtering course, under supervision of Dr. Parsa.
Abstract—High performance tracking of an industrial robot depends on accurate expression of manipulator dynamics. When a robot has flexible joints efficient model parametrization will be difficult to achieve. In this course project report an extended Kalman filter (EKF) observer to estimate manipulator states is presented. In a computer simulation the estimation performance is demonstrated. Experimental setup for KUKA/DLR Light-Weight robot in Human Robot Interaction at the University of Western Ontario is also carried out without any success.
Documents and MATLAB and Maple files can be downloaded here.