  We present an empirical investigation of a new mapping system based on a
graph of panoramic depth images. Panoramic images efficiently capture range
measurements taken by a spinning lidar sensor, recording fine detail on the
order of a few centimeters within maps of expansive scope on the order of tens
of millions of cubic meters. The flexibility of the system is demonstrated by
running the same mapping software against data collected by hand-carrying a
sensor around a laboratory space at walking pace, moving it outdoors through a
campus environment at running pace, driving the sensor on a small wheeled
vehicle on- and off-road, flying the sensor through a forest, carrying it on
the back of a legged robot navigating an underground coal mine, and mounting it
on the roof of a car driven on public roads. The full 3D maps are built online
with a median update time of less than ten milliseconds on an embedded NVIDIA
Jetson AGX Xavier system.
