Visual-inertial Mapping
Visual-Inertial Mapping is a simultaneous localization and mapping (SLAM) methodology that fuses visual data from cameras and inertial measurements from an inertial measurement unit to estimate camera motion and reconstruct 3D environments, distinguished by its integration of complementary visual and inertial sensory modalities for improved accuracy, robustness, and scalability in dynamic and texture-deprived scenarios.
152
Publications
15.1K
Citations
533
Authors
170
Institutions
Publications per year
2017–2026
121
Parents
152
Robust visual inertial odometry using a direct EKF-based approach
Michael Bloesch, Sammy Omari, Marco Hutter et al. · 2015 · 785 citations
LVI-SAM: Tightly-coupled Lidar-Visual-Inertial Odometry via Smoothing and Mapping
Tixiao Shan, Brendan Englot, Carlo Ratti et al. · 2021 · 516 citations
1–5 of 152
533
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Hong Kong University of Science and Technology, Hong Kong SAR China
5 publications · 375 citations
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5
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4
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4
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1–5 of 533
170
ETH Zurich
Zurich, Switzerland
14 h-index
61 publications
17.6K citations

Hong Kong University of Science and Technology
Hong Kong, Hong Kong
7 h-index
25 publications
1.2K citations
Technical University of Munich
Munich, Germany
5 h-index
18 publications
1.4K citations
University of Chinese Academy of Sciences
Beijing, China
5 h-index
12 publications
479 citations
Wuhan University
Wuhan, China
5 h-index
14 publications
477 citations
Massachusetts Institute of Technology
Cambridge, United States
5 h-index
12 publications
2K citations

Zhejiang University
Hangzhou, China
4 h-index
12 publications
913 citations
University of South Carolina
Columbia, United States
4 h-index
11 publications
738 citations
1–8 of 170
17 publications · 2.2K citations
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IJRR · 6 publications · 2K citations
6
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6 publications · 202 citations
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6 publications · 191 citations
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Repository · 5 publications · 141 citations
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