Direct Visual-Inertial Odometry with Stereo Cameras

Vladyslav Usenko, Jakob Engel, Jörg Stückler, Daniel Cremers
IEEE International Conference on Robotics and Automation (ICRA), 2016

We propose a novel direct visual-inertial odometry method for stereo cameras. Camera pose, velocity and IMU biases are simultaneously estimated by minimizing a combined photometric and inertial energy functional. This allows us to exploit the complementary nature of vision and inertial data. At the same time, and in contrast to all existing visual-inertial methods, our approach is fully direct: geometry is estimated in the form of semi-dense depth maps instead of manually designed sparse keypoints. Depth information is obtained both from static stereo – relating the fixed-baseline images of the stereo camera – and temporal stereo – relating images from the same camera, taken at different points in time. We show that our method outperforms not only vision-only or loosely coupled approaches, but also can achieve more accurate results than state-of-the-art keypoint-based methods on different datasets, including rapid motion and significant illumination changes. In addition, our method provides high-fidelity semi-dense, metric reconstructions of the environment, and runs in real-time on a CPU.


» Show BibTeX
@InProceedings{usenko16icra, title = "Direct Visual-Inertial Odometry with Stereo Cameras", author = "V. Usenko and J. Engel and J. Stueckler and D. Cremers", booktitle = {Int. Conf. on Robotics and Automation}, year = "2016", }



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