The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Information fusion in navigation systems via factor graph based incremental smoothing
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Citations
Cites
Multiple View Geometry in Computer Vision
Hartley, R., & Zisserman, A. (2004) · doi:10.1017/cbo9780511811685 · Cited by 21,070
Are we ready for autonomous driving? The KITTI vision benchmark suite
Geiger, A., Lenz, P., & Urtasun, R. (2012) · 2012 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2012.6248074 · Cited by 14,897
Factor graphs and the sum-product algorithm
Kschischang, F. R., Frey, B. J., & Loeliger, H.-A. (2001) · IEEE Transactions on Information Theory · doi:10.1109/18.910572 · Cited by 6,486 · cited 2×
“We represent the information fusion problem using a graphical model known as a factor graph [15].”
Parallel Tracking and Mapping for Small AR Workspaces
Klein, G., & Murray, D. (2007) · 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality · doi:10.1109/ismar.2007.4538852 · Cited by 4,346
DTAM: Dense tracking and mapping in real-time
Newcombe, R. A., Lovegrove, S. J., & Davison, A. J. (2011) · 2011 International Conference on Computer Vision · doi:10.1109/iccv.2011.6126513 · Cited by 2,078 · cited 1×
“Several parallel processing data fusion techniques have been introduced recently [28,7,29], including a factor-graph based architecture [30] that utilizes incremental smoothing internally.”
MethodiSAM2: Incremental smoothing and mapping using the Bayes tree
Kaess, M., Johannsson, H., Roberts, R., Ila, V., Leonard, J. J., & Dellaert, F. (2012) · The International Journal of Robotics Research · doi:10.1177/0278364911430419 · Cited by 1,362
Self-citationGlobally Consistent Range Scan Alignment for Environment Mapping
Lu, F., & Milios, E. (1997) · Autonomous Robots · doi:10.1023/a:1008854305733 · Cited by 1,304
Cited by
On-Manifold Preintegration for Real-Time Visual--Inertial Odometry
Forster, C., Carlone, L., Dellaert, F., & Scaramuzza, D. (2017) · IEEE Transactions on Robotics · doi:10.1109/tro.2016.2597321 · Cited by 1,502
Self-citationIMU Preintegration on Manifold for Efficient Visual-Inertial Maximum-a-Posteriori Estimation
Forster, C., Carlone, L., Dellaert, F., & Scaramuzza, D. (2015) · Robotics: Science and Systems XI · doi:10.15607/rss.2015.xi.006 · Cited by 499
Self-citationFactor graph optimization for GNSS/INS integration: A comparison with the extended Kalman filter
Wen, W., Pfeifer, T., Bai, X., & Hsu, L. (2021) · NAVIGATION · doi:10.1002/navi.421 · Cited by 259
Graph-based terrain relative navigation with optimal landmark database selection
Steiner, T. J., Brady, T. M., & Hoffman, J. A. (2015) · 2015 IEEE Aerospace Conference · doi:10.1109/aero.2015.7119053 · Cited by 16
Williams, S., Indelman, V., Kaess, M., Roberts, R., Leonard, J. J., & Dellaert, F. (2014) · The International Journal of Robotics Research · doi:10.1177/0278364914531056 · Cited by 2
Self-citation
Metadata
- Authors
- Indelman, V., Williams, S., Kaess, M., & Dellaert, F.
- Venue
- Robotics and Autonomous Systems
- Publisher
- Elsevier BV
- Published
- 2013-08
- Volume
- 61
- Issue
- 8
- Pages
- 721-738
- ISSN
- 0921-8890 (ISSN-L)
- OpenAlex
- W2017489593
- Cited by
- 271
- References
- 7
- FWCI
- 22.51
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Information fusion in navigation systems via factor graph based incremental smoothing. https://app.cochat.ai/papers/10.1016/j.robot.2013.05.001
- The paper
- Indelman, V., Williams, S., Kaess, M., & Dellaert, F. (2013). Information fusion in navigation systems via factor graph based incremental smoothing. Robotics and Autonomous Systems. https://doi.org/10.1016/j.robot.2013.05.001
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
