Multi-level mapping: Real-time dense monocular SLAM
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Roy_Multi-level mapping.pdf
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1.33 MB
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Author(s)
Greene, William N.
Ok, Kyel
Lommel, Peter H.
Roy, Nicholas
Date Issued
June 2016
Journal
2016 IEEE International Conference on Robotics and Automation (ICRA)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Greene, W. Nicholas, Kyel Ok, Peter Lommel, and Nicholas Roy. “Multi-Level Mapping: Real-Time Dense Monocular SLAM.” 2016 IEEE International Conference on Robotics and Automation (ICRA), 16-20 May 2016, Stockholm, Sweden, IEEE, 2016.
Version
Author's final manuscript
Abstract
We present a method for Simultaneous Localization and Mapping (SLAM) using a monocular camera that is capable of reconstructing dense 3D geometry online without the aid of a graphics processing unit (GPU). Our key contribution is a multi-resolution depth estimation and spatial smoothing process that exploits the correlation between low-texture image regions and simple planar structure to adaptively scale the complexity of the generated keyframe depthmaps to the texture of the input imagery. High-texture image regions are represented at higher resolutions to capture fine detail, while low-texture regions are represented at coarser resolutions for smooth surfaces. The computational savings enabled by this approach allow for significantly increased reconstruction density and quality when compared to the state-of-the-art. The increased depthmap density also improves tracking performance as more constraints can contribute to the pose estimation. A video of experimental results is available at http://groups.csail.mit.edu/rrg/multi_level_mapping.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1109/ICRA.2016.7487213
