Particle filter based tracking of free-swinging objects for visual servoing

Abstract

We present a visual servoing system for the synchronization of a robot with a dynamic rigid body using a particle filter-based state estimator. We experimentally demonstrate its application for robotic loading of parts onto oscillating hangers in an industrial paint line. The particle filter is implemented with a physical dynamical model of the hanger, using the Euler equations for a pendulum with three degrees of freedom. The visual servoing system is successfully demonstrated using two cameras to get a good 3D estimate of the hanger motion. The experimental results indicate a maximum tracking error of 0.1 degrees.