Publication
Realtime Perception for Catching a Flying Ball with a Mobile Humanoid
Oliver Birbach; Udo Frese; Berthold Bäuml
In: Proceedings of the IEEE International Conference on Robotics and Automation. IEEE International Conference on Robotics and Automation (ICRA-11), May 9-13, Shanghai, China, Pages 5955-5962, IEEE, 5/2011.
Abstract
This paper presents a realtime perception system for catching flying
balls with DLR's humanoid Rollin' Justin. We use a
two-staged bottom up approach in which we first detect balls as circles
and feed these measurements into a multiple hypothesis
tracker (MHT). The novel circle detection scheme
works in realistic scenes without tuning parameters or background
assumptions. We extend the classical
multi-hypothesis tracking with prior information about the expected
trajectories, therefore limiting the number of hypotheses in the first
place. Since the robot starts moving while the ball is still tracked,
the cameras shake heavily. A 6-DOF inertial measurements unit (IMU) is integrated to compensate this
motion. Using ground-truth from a marker based tracking system we evaluate the metrical accuracy of the
motion compensation as well as the tracker's prediction accuracy while
in motion.