Concurrent filtering and smoothing
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Leonard_Concurrent filtering.pdf
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474.18 KB
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Author(s)
Kaess, Michael
Williams, Stephen
Indelman, Vadim
Roberts, Richard
Leonard, John Joseph
Dellaert, Frank
Date Issued
July 2012
Journal
Proceedings of the 2012 15th International Conference on Information Fusion (FUSION)
Publisher
Institute of Electrical and Electronics Engineers
Citation
Kaess, Michael, Stephen Williams, Vadim Indelman, Richard Roberts, John J. Leonard, and Frank Dellaert. "Concurrent Filtering and Smoothing." In 2012 15th International Conference on Information Fusion (FUSION), 9-12 July 2012, Singapore. p.1300-1307
Version
Author's final manuscript
Abstract
This paper presents a novel algorithm for integrating real-time filtering of navigation data with full map/trajectory smoothing. Unlike conventional mapping strategies, the result of loop closures within the smoother serve to correct the real-time navigation solution in addition to the map. This solution views filtering and smoothing as different operations applied within a single graphical model known as a Bayes tree. By maintaining all information within a single graph, the optimal linear estimate is guaranteed, while still allowing the filter and smoother to operate asynchronously. This approach has been applied to simulated aerial vehicle sensors consisting of a high-speed IMU and stereo camera. Loop closures are extracted from the vision system in an external process and incorporated into the smoother when discovered. The performance of the proposed method is shown to approach that of full batch optimization while maintaining real-time operation.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Mechanical Engineering
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike 3.0
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DOI of Published Version
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6289957
