A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is
PROBE: Predictive robust estimation for visual-inertial navigation
2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Navigation in unknown, chaotic environments continues to present a significant challenge for the robotics community. Lighting changes, self-similar textures, motion blur, and moving objects are all considerable stumbling blocks for state-of-the-art vision-based navigation algorithms. In this paper we present a novel technique for improving localization accuracy within a visual-inertial navigation system (VINS). We make use of training data to learn a model for the quality of visual featuresdoi:10.1109/iros.2015.7353890 dblp:conf/iros/PeretroukhinCGK15 fatcat:auoyludkbzbkzay7a7ksnlctsi