A Robust Multi-Stereo Visual-Inertial Odometry Pipeline
Joshua Jaekel,Joshua G. Mangelson,Sebastian Scherer,Michael Kaess,Joshua Jaekel,Joshua G. Mangelson,Sebastian Scherer,Michael Kaess
In this paper we present a novel multi-stereo visual-inertial odometry (VIO) framework which aims to improve the robustness of a robot's state estimate during aggressive motion and in visually challenging environments. Our system uses a fixed-lag smoother which jointly optimizes for poses and landmarks across all stereo pairs. We propose a 1-point RANdom SAmple Consensus (RANSAC) algorithm which i...
