  Recovering the pose of an object from mere point clouds is often hindered by
the lack of the information that they provide. In this lab, we address this
problem by proposing a method that exploits the symmetry of objects as well as
using pictures taken from a static camera of the same scene. We apply this
approach to detects nuts in a table top scene that includes screws, nuts,
washers and several placeholders for grasp planning.
