Robust real-time visual odometry for dense RGB-D mapping
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Leonard_Robust real-time.pdf
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Author(s)
Whelan, Thomas
Johannsson, Hordur
Kaess, Michael
McDonald, John
Leonard, John Joseph
Date Issued
May 2013
Journal
Proceedings of the 2013 IEEE International Conference on Robotics and Automation
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Whelan, Thomas, Hordur Johannsson, Michael Kaess, John J. Leonard, and John McDonald. “Robust Real-Time Visual Odometry for Dense RGB-D Mapping.” 2013 IEEE International Conference on Robotics and Automation (May 2013).
Version
Author's final manuscript
Abstract
This paper describes extensions to the Kintinuous [1] algorithm for spatially extended KinectFusion, incorporating the following additions: (i) the integration of multiple 6DOF camera odometry estimation methods for robust tracking; (ii) a novel GPU-based implementation of an existing dense RGB-D visual odometry algorithm; (iii) advanced fused realtime surface coloring. These extensions are validated with extensive experimental results, both quantitative and qualitative, demonstrating the ability to build dense fully colored models of spatially extended environments for robotics and virtual reality applications while remaining robust against scenes with challenging sets of geometric and visual features.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Mechanical Engineering
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1109/ICRA.2013.6631400
