Visual-Inertial Navigation is a robotic navigation framework that fuses visual data from cameras and inertial measurements from IMUs to jointly estimate ego-motion and scene structure, distinguishing itself from purely visual or inertial methods through complementary sensor integration for improved accuracy and robustness.
441
Publications
26.9K
Citations
1.2K
Authors
322
Institutions
Publications per year
2017–2026
266
Variants
VinsVisual-inertial Navigation System
Publications
441
Robust visual inertial odometry using a direct EKF-based approach
Michael Bloesch, Sammy Omari, Marco Hutter et al. · 2015 · 785 citations
OpenVINS: A Research Platform for Visual-Inertial Estimation
Patrick Geneva, Kevin Eckenhoff, Woosik Lee et al. · 2020 · 623 citations
1–5 of 441
Authors
1.2K
- GH
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- SI
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- AI
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1–5 of 1.2K
Institutions
322
University of Delaware
Newark, United States
21 h-index
74 publications
6.8K citations
ETH Zurich
Zurich, Switzerland
20 h-index
83 publications
17.5K citations
Massachusetts Institute of Technology
Cambridge, United States
17 h-index
65 publications
4.3K citations
University of Minnesota
Minneapolis, United States
16 h-index
46 publications
8.3K citations
Wuhan University
Wuhan, China
14 h-index
72 publications
3.3K citations
Jet Propulsion Laboratory
Pasadena, United States
10 h-index
48 publications
2.7K citations
Georgia Institute of Technology
Atlanta, United States
10 h-index
24 publications
2.4K citations
University of California, Riverside
Riverside, United States
9 h-index
18 publications
3K citations
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Venues
- IEEE Robotics and Automation Letters
28 publications · 1.7K citations
20
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- Sensors
16 publications · 376 citations
14
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- IEEE Sensors Journal
16 publications · 554 citations
14
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- Journal of Field Robotics
JFR · 13 publications · 1.1K citations
13
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- IEEE Transactions on Robotics
12 publications · 1.8K citations
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