Uncertainty Reduction Using Dynamics

M. Moll and M. A. Erdmann, “Uncertainty Reduction Using Dynamics,” in Proc. 2000 IEEE Intl. Conf. on Robotics and Automation, San Francisco, California, 2000, pp. 3673–3680.

Abstract

For assembly tasks parts often have to be oriented before they can be put in an assembly. The results presented in this paper are a component of the automated design of parts orienting devices. The focus is on orienting parts with minimal sensing and manipulation. We present a new approach to parts orienting through the manipulation of pose distributions. Through dynamic simulation we can determine the pose distribution for an object being dropped from an arbitrary height on an arbitrary surface. By varying the drop height and the shape of the support surface we can find the initial conditions that will result in a pose distribution with minimal entropy. We are trying to uniquely orient a part with high probability just by varying the initial conditions. We will derive a condition on the pose and velocity of an object in contact with a sloped surface that will allow us to quickly determine the final resting configuration of the object. This condition can then be used to quickly compute the pose distribution. We also show simulation and experimental results that confirm that our dynamic simulator can be used to find the true pose distribution of an object.

Publisher: http://dx.doi.org/10.1109/ROBOT.2000.845304

PDF preprint: http://kavrakilab.org/publications/moll-erdmann2000uncertainty-reduction-using.pdf