火星探査向けイベントカメラオドメトリの探求
Exploring Event Camera-based Odometry for Planetary Robots
イベントカメラとフィルタベースのバックエンドを組み合わせたEKLT-VIOを提案し、火星探査に適した高精度・高ロバストな視覚慣性オドメトリを実現した。
著者: Florian Mahlknecht, Daniel Gehrig, Jeremy Nash, Friedrich M. Rockenbauer, Benjamin Morrell, Jeff Delaune, Davide Scaramuzza
分類: cs.CV, cs.RO
原文アブストラクト
Due to their resilience to motion blur and high robustness in low-light and high dynamic range conditions, event cameras are poised to become enabling sensors for vision-based exploration on future Mars helicopter missions. However, existing event-based visual-inertial odometry (VIO) algorithms either suffer from high tracking errors or are brittle, since they cannot cope with significant depth uncertainties caused by an unforeseen loss of tracking or other effects. In this work, we introduce EKLT-VIO, which addresses both limitations by combining a state-of-the-art event-based frontend with a filter-based backend. This makes it both accurate and robust to uncertainties, outperforming event- and frame-based VIO algorithms on challenging benchmarks by 32%. In addition, we demonstrate accurate performance in hover-like conditions (outperforming existing event-based methods) as well as high robustness in newly collected Mars-like and high-dynamic-range sequences, where existing frame-based methods fail. In doing so, we show that event-based VIO is the way forward for vision-based exploration on Mars.
