Stable Adaptive Extended Kalman Filter for Estimating Robot Link Velocity and Acceleration
Published in IEEE IROS, 2023
Robot manipulators link velocity and acceleration can be estimated using nonlinear observers. This is done by model-based fusion of inertial measurement units (IMUs) with the robot motor encoders. This method has been proven to be light, generally applicable (broad bandwidth) and easily implementable. In order to further improve the estimation accuracy while running the system, we propose to adapt the noise information in this paper. This would automatically reduce the system vulnerability to imperfect modelings and sensor changes. Moreover, viable strategies to maintain the system stability are introduced. Finally we fully evaluate the overall framework with a seven DoF robot manipulator, whose links are equipped with IMUs.