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

Authors

533

  1. RS
    Roland Siegwart

    ETH Zurich, Switzerland

    8 publications · 3.4K citations

    8

    h-index

  2. SS
    Shaojie Shen

    Hong Kong University of Science and Technology, Hong Kong SAR China

    5 publications · 375 citations

    5

    h-index

  3. DS
    Davide Scaramuzza

    University of Zurich, Switzerland

    5 publications · 257 citations

    5

    h-index

  4. MB
    Michael Bloesch

    ETH Zurich, Switzerland

    4 publications · 1.3K citations

    4

    h-index

  5. IR
    Ioannis Rekleitis

    McGill University, Canada

    4 publications · 240 citations

    4

    h-index

1–5 of 533

Venues

  1. IEEE Robotics and Automation Letters

    17 publications · 2.2K citations

    16

    h-index

  2. The International Journal of Robotics Research

    IJRR · 6 publications · 2K citations

    6

    h-index

  3. Sensors

    6 publications · 202 citations

    6

    h-index

  4. IEEE Access

    6 publications · 191 citations

    6

    h-index

  5. arXiv (Cornell University)

    Repository · 5 publications · 141 citations

    5

    h-index

1–5