Reflection-Robust Stereo Visual-Inertial Odometry via Kalman-Filtered Ground-Height Estimation

1. 05:00
   arXiv Robotics — research abstractsSignal

   Reflection-Robust Stereo Visual-Inertial Odometry via Kalman-Filtered Ground-Height Estimation

   This research presents a method for stereo visual-inertial odometry that addresses unreliable feature associations caused by specular reflections on indoor floors. Instead of suppressing all floor-region features, the proposed approach estimates ground height in real time using a scalar Kalman filter with Normalized Innovation Squared (NIS) gating and rejects only feature candidates whose inferred 3D positions fall below the estimated ground height within reflection-prone regions. Experiments on real reflective-floor indoor sequences demonstrate improved trajectory accuracy in reflection-dominant environments while maintaining accurate ground-height estimates and recovering from actual ground-height changes.

Current attention 3·Peak within the comparable range 3（2026-11-06 22:00 UTC）·Change within the comparable range over 24 hours –

The trend compares participants observed continuously; its scope may be narrower than current attention totals. Hover or click to explore hourly observations, or use the left and right arrow keys.