A comparative study of unscented and extended Kalman filter for position and velocity estimation of Stewart platform manipulator

The estimation of position and velocity of Stewart Manipulator using low cost inertial sensors (accelerometers and gyroscope) and Leg length measurements will be considered. The estimation is based on the integration of different sensors by means of Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF). The results of the evaluation of these filter estimation techniques are compared with each other. A proposed computed torque controller is simulated and verified using the estimated states from UKF with 6 degrees of freedom Stewart platform using MATLAB SimMechanics toolbox.