  We present a local 3D voxel mapping framework for off-road path planning and
navigation. Our method provides both hard and soft positive obstacle detection,
negative obstacle detection, slope estimation, and roughness estimation. By
using a 3D array lookup table data structure and by leveraging the GPU it can
provide online performance. We then demonstrate the system working on three
vehicles, a Clearpath Robotics Warthog, Moose, and a Polaris Ranger, and
compare against a set of pre-recorded waypoints. This was done at 4.5 m/s in
autonomous operation and 12 m/s in manual operation with a map update rate of
10 Hz. Finally, an open-source ROS implementation is provided.
https://github.com/unmannedlab/G-VOM
