  This paper presents BURG-Toolkit, a set of open-source tools for Benchmarking
and Understanding Robotic Grasping. Our tools allow researchers to: (1) create
virtual scenes for generating training data and performing grasping in
simulation; (2) recreate the scene by arranging the corresponding objects
accurately in the physical world for real robot experiments, supporting an
analysis of the sim-to-real gap; and (3) share the scenes with other
researchers to foster comparability and reproducibility of experimental
results. We explain how to use our tools by describing some potential use
cases. We further provide proof-of-concept experimental results quantifying the
sim-to-real gap for robot grasping in some example scenes. The tools are
available at: https://mrudorfer.github.io/burg-toolkit/
