Factor Graph Optimization
Factor Graph Optimization is a probabilistic graphical model-based inference method that formulates estimation problems by factorizing joint probability distributions into variable nodes and factor nodes to enable efficient, structured optimization over nonlinear and non-Gaussian measurement models in inertial geodesy.
255
Publications
15.3K
Citations
751
Authors
244
Institutions
Publications per year
2017–2026
169
Parents
255
LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping
Tixiao Shan, Brendan Englot, Drew Meyers et al. · 2020 · 2K citations
On-Manifold Preintegration for Real-Time Visual--Inertial Odometry
Christian Förster, Luca Carlone, Frank Dellaert et al. · IEEE Transactions on Robotics · 2016 · 1.4K citations · Full text
Factor Graphs for Robot Perception
Frank Dellaert, Michael Kaess · Foundations and Trends in Robotics · 2017 · 414 citations
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244
Massachusetts Institute of Technology
Cambridge, United States
16 h-index
44 publications
13.4K citations

Hong Kong Polytechnic University
Hong Kong, Hong Kong
16 h-index
40 publications
2.5K citations
Georgia Institute of Technology
Atlanta, United States
14 h-index
39 publications
6K citations
Carnegie Mellon University
Pittsburgh, United States
13 h-index
31 publications
2.4K citations
Wuhan University
Wuhan, China
12 h-index
53 publications
2.3K citations
Tsinghua University
Beijing, China
9 h-index
23 publications
736 citations
University of Michigan
Ann Arbor, United States
7 h-index
17 publications
740 citations

Beijing Institute of Technology
Beijing, China
6 h-index
25 publications
656 citations
1–8 of 244
19 publications · 1.3K citations
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9 publications · 295 citations
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9 publications · 194 citations
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Repository · 8 publications · 241 citations
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9 publications · 290 citations
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