Spectral Measurement Sparsification for Pose-Graph SLAM
2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) October 23-27, 2022, Kyoto, Japan
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024
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| Online Access: | https://hdl.handle.net/1721.1/153749 |
| _version_ | 1811082774114729984 |
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| author | Doherty, Kevin J. Rosen, David M. Leonard, John J. |
| author2 | Massachusetts Institute of Technology. Department of Mechanical Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Mechanical Engineering Doherty, Kevin J. Rosen, David M. Leonard, John J. |
| author_sort | Doherty, Kevin J. |
| collection | MIT |
| description | 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) October 23-27, 2022, Kyoto, Japan |
| first_indexed | 2024-09-23T12:08:47Z |
| format | Article |
| id | mit-1721.1/153749 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T12:08:47Z |
| publishDate | 2024 |
| publisher | IEEE |
| record_format | dspace |
| spelling | mit-1721.1/1537492024-09-20T18:49:26Z Spectral Measurement Sparsification for Pose-Graph SLAM Doherty, Kevin J. Rosen, David M. Leonard, John J. Massachusetts Institute of Technology. Department of Mechanical Engineering 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) October 23-27, 2022, Kyoto, Japan Simultaneous localization and mapping (SLAM) is a critical capability in autonomous navigation, but in order to scale SLAM to the setting of "lifelong" SLAM, particularly under memory or computation constraints, a robot must be able to determine what information should be retained and what can safely be forgotten. In graph-based SLAM, the number of edges (measurements) in a pose graph determines both the memory requirements of storing a robot's observations and the computational expense of algorithms deployed for performing state estimation using those observations; both of which can grow unbounded during long-term navigation. To address this, we propose a spectral approach for pose graph sparsification which maximizes the algebraic connectivity of the sparsified measurement graphs, a key quantity which has been shown to control the estimation error of pose graph SLAM solutions. Our algorithm, MAC (for "maximizing algebraic connectivity"), which is based on convex relaxation, is simple and computationally inexpensive, and admits formal post hoc performance guarantees on the quality of the solutions it provides. In experiments on benchmark pose-graph SLAM datasets, we show that our approach quickly produces high-quality sparsification results which retain the connectivity of the graph and, in turn, the quality of corresponding SLAM solutions, as compared to a baseline approach which does not consider graph connectivity. 2024-03-13T19:11:18Z 2024-03-13T19:11:18Z 2022-10-23 2024-03-13T18:59:55Z Article http://purl.org/eprint/type/ConferencePaper https://hdl.handle.net/1721.1/153749 Doherty, Kevin J., Rosen, David M. and Leonard, John J. 2022. "Spectral Measurement Sparsification for Pose-Graph SLAM." en 10.1109/iros47612.2022.9981584 Creative Commons Attribution-Noncommercial-ShareAlike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf IEEE arxiv |
| spellingShingle | Doherty, Kevin J. Rosen, David M. Leonard, John J. Spectral Measurement Sparsification for Pose-Graph SLAM |
| title | Spectral Measurement Sparsification for Pose-Graph SLAM |
| title_full | Spectral Measurement Sparsification for Pose-Graph SLAM |
| title_fullStr | Spectral Measurement Sparsification for Pose-Graph SLAM |
| title_full_unstemmed | Spectral Measurement Sparsification for Pose-Graph SLAM |
| title_short | Spectral Measurement Sparsification for Pose-Graph SLAM |
| title_sort | spectral measurement sparsification for pose graph slam |
| url | https://hdl.handle.net/1721.1/153749 |
| work_keys_str_mv | AT dohertykevinj spectralmeasurementsparsificationforposegraphslam AT rosendavidm spectralmeasurementsparsificationforposegraphslam AT leonardjohnj spectralmeasurementsparsificationforposegraphslam |