Measurement Error Detection for Stereo Visual Odometry Integrity

Abstract

Integrity, a safety-of-life framework from civil aviation for satellite navigation, is greatly under-explored in visual navigation. A new two-factor approach to rejecting measurement outliers is proposed for navigation integrity in stereo visual odometry (VO). In contrast to other treatments using reprojection error as measurement residuals, our choice of landmark matching error inherently connects navigation solutions and integrity monitoring. We propose two methods to detect large measurement residuals that cannot otherwise be identified by existing outlier rejection methods in state-of-the-art VO pipelines. By rejecting these outliers, measurement residuals can be bounded by the distribution overbounding method that provides fundamental inputs for integrity computations. We evaluate our methods using an open-source data set. Overbounding performance is improved in terms of tightness, computational efficiency, and most important of all, scenario tolerance. This could be a good starting point for developing future integrity monitoring algorithms for visual navigation and in particular, stereo VO.