Real-Time Marker-Based Tracking and Pose Estimation for a Rotating Object Using High-Speed Vision

Abstract

Object tracking and pose estimation have always been challenging tasks in robotics, particularly for rotating objects. Rotating objects move quickly and with complex pose variations. In this study, we introduce a marker-based tracking and pose estimation method for rotating objects using a high-speed vision system. The method can obtain pose information at frequencies greater than 500 Hz, and can still estimate the pose when parts of the markers are lost during tracking. A robot catching experiment shows that the accuracy and frequency of this system are capable of high-speed tracking tasks.