Underwater Visual Slam

Underwater Visual SLAM is a simultaneous localization and mapping framework that integrates visual sensing data from underwater environments to concurrently estimate the trajectory of a submerged vehicle and reconstruct its surrounding scene geometry, distinguished by its adaptation to the challenging optical properties and limited visibility conditions inherent to aquatic media.

104

Publications

4.9K

Citations

263

Authors

105

Institutions

Publications per year

2017–2026

59

Authors

263

  1. RM
    Ryan M. Eustice

    University of Michigan, United States

    12 publications · 897 citations

    12

    h-index

  2. AK
    Ayoung Kim

    Korea Advanced Institute of Science and Technology, South Korea

    7 publications · 531 citations

    7

    h-index

  3. FB
    Francisco Bonin‐Font

    Universitat de les Illes Balears, Spain

    5 publications · 118 citations

    5

    h-index

  4. YP
    Yvan Pétillot

    Heriot-Watt University, United Kingdom

    5 publications · 162 citations

    5

    h-index

  5. JS
    Joaquím Salví

    Universitat de Girona, Spain

    5 publications · 135 citations

    5

    h-index

1–5 of 263

Venues

  1. Autonomous Robots

    8 publications · 567 citations

    8

    h-index

  2. Journal of Intelligent & Robotic Systems

    6 publications · 123 citations

    6

    h-index

  3. Ocean Engineering

    4 publications · 213 citations

    5

    h-index

  4. Robotics and Autonomous Systems

    4 publications · 286 citations

    4

    h-index

  5. Intelligent Service Robotics

    3 publications · 86 citations

    3

    h-index

1–5