  Traveling at constant velocity is the most efficient trajectory for most
robotics applications. Unfortunately without accelerometer excitation,
monocular Visual-Inertial Odometry (VIO) cannot observe scale and suffers
severe error drift. This was the main motivation for incorporating a 1D laser
range finder in the navigation system for NASA's Ingenuity Mars Helicopter.
However, Ingenuity's simplified approach was limited to flat terrains. The
current paper introduces a novel range measurement update model based on using
facet constraints. The resulting range-VIO approach is no longer limited to
flat scenes, but extends to any arbitrary structure for generic robotic
applications. An important theoretical result shows that scale is no longer in
the right nullspace of the observability matrix for zero or constant
acceleration motion. In practical terms, this means that scale becomes
observable under constant-velocity motion, which enables simple and robust
autonomous operations over arbitrary terrain. Due to the small range finder
footprint, range-VIO retains the minimal size, weight, and power attributes of
VIO, with similar runtime. The benefits are evaluated on real flight data
representative of common aerial robotics scenarios. Robustness is demonstrated
using indoor stress data and fullstate ground truth. We release our software
framework, called xVIO, as open source.
