  Interactive 3D simulations have enabled breakthroughs in robotics and
computer vision, but simulating the broad diversity of environments needed for
deep learning requires large corpora of photo-realistic 3D object models. To
address this need, we present Google Scanned Objects, an open-source collection
of over one thousand 3D-scanned household items released under a Creative
Commons license; these models are preprocessed for use in Ignition Gazebo and
the Bullet simulation platforms, but are easily adaptable to other simulators.
We describe our object scanning and curation pipeline, then provide statistics
about the contents of the dataset and its usage. We hope that the diversity,
quality, and flexibility of Google Scanned Objects will lead to advances in
interactive simulation, synthetic perception, and robotic learning.
