Deformation-based loop closure for large scale dense RGB-D SLAM
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Leonard_Deformation-based loop.pdf
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1.57 MB
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Author(s)
Whelan, Thomas
Kaess, Michael
McDonald, John
Leonard, John Joseph
Date Issued
November 2013
Journal
Proceedings of the 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Whelan, Thomas, Michael Kaess, John J. Leonard, and John McDonald. “Deformation-Based Loop Closure for Large Scale Dense RGB-D SLAM.” 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (November 2013).
Version
Author's final manuscript
Abstract
In this paper we present a system for capturing large scale dense maps in an online setting with a low cost RGB-D sensor. Central to this work is the use of an “as-rigid-as-possible” space deformation for efficient dense map correction in a pose graph optimisation framework. By combining pose graph optimisation with non-rigid deformation of a dense map we are able to obtain highly accurate dense maps over large scale trajectories that are both locally and globally consistent. With low latency in mind we derive an incremental method for deformation graph construction, allowing multi-million point maps to be captured over hundreds of metres in real-time. We provide benchmark results on a well established RGB-D SLAM dataset demonstrating the accuracy of the system and also provide a number of our own datasets which cover a wide range of environments, both indoors, outdoors and across multiple floors.
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
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/IROS.2013.6696405
