  We present TartanDrive 2.0, a large-scale off-road driving dataset for
self-supervised learning tasks. In 2021 we released TartanDrive 1.0, which is
one of the largest datasets for off-road terrain. As a follow-up to our
original dataset, we collected seven hours of data at speeds of up to 15m/s
with the addition of three new LiDAR sensors alongside the original camera,
inertial, GPS, and proprioceptive sensors. We also release the tools we use for
collecting, processing, and querying the data, including our metadata system
designed to further the utility of our data. Custom infrastructure allows end
users to reconfigure the data to cater to their own platforms. These tools and
infrastructure alongside the dataset are useful for a variety of tasks in the
field of off-road autonomy and, by releasing them, we encourage collaborative
data aggregation. These resources lower the barrier to entry to utilizing
large-scale datasets, thereby helping facilitate the advancement of robotics in
areas such as self-supervised learning, multi-modal perception, inverse
reinforcement learning, and representation learning. The dataset is available
at https://github.com/castacks/tartan drive 2.0.
