A robust optical/inertial data fusion system for motion tracking of the robot manipulator

Abstract

We present an optical/inertial data fusion system for motion tracking of the robot manipulator, which is proved to be more robust and accurate than a normal optical tracking system (OTS). By data fusion with an inertial measurement unit (IMU), both robustness and accuracy of OTS are improved. The Kalman filter is used in data fusion. The error distribution of OTS provides an important reference on the estimation of measurement noise using the Kalman filter. With a proper setup of the system and an effective method of coordinate frame synchronization, the results of experiments show a significant improvement in terms of robustness and position accuracy.