Range-Visual-Inertial Odometry: Scale Observability Without Excitation

TL;DR

This paper introduces a novel range-VIO method that enables scale observability during constant-velocity motion, extending VIO capabilities to arbitrary terrains with minimal added size, weight, and power.

Contribution

It presents a new range measurement update model using facet constraints, making scale observable in VIO during constant-velocity motion, unlike previous methods limited to flat terrains.

Findings

Scale becomes observable during constant-velocity motion.

Range-VIO performs well on real aerial robotics data.

Open source software xVIO is released for community use.

Abstract

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.