  Anatomical models of a medical robot's environment can significantly help
guide design and development of a new robotic system. These models can be used
for benchmarking motion planning algorithms, evaluating controllers, optimizing
mechanical design choices, simulating procedures, and even as resources for
data generation. Currently, the time-consuming task of generating these
environments is repeatedly performed by individual research groups and rarely
shared broadly. This not only leads to redundant efforts, but also makes it
challenging to compare systems and algorithms accurately. In this work, we
present a collection of clinically-relevant anatomical environments for medical
robots operating in the lungs. Since anatomical deformation is a fundamental
challenge for medical robots operating in the lungs, we describe a way to model
respiratory deformation in these environments using patient-derived data. We
share the environments and deformation data publicly by adding them to the
Medical Robotics Anatomical Dataset (Med-RAD), our public dataset of anatomical
environments for medical robots.
