Underwater Slam

Underwater SLAM is a computational framework for simultaneous localization and mapping that specifically enables autonomous underwater vehicles to construct consistent environmental models and estimate their own position within unstructured subsea environments using sparse and noisy sensor data.

157

Publications

7.6K

Citations

426

Authors

154

Institutions

Publications per year

2017–2026

56

Variants

Underwater Simultaneous Localization And Mapping

Authors

426

  1. RM
    Ryan M. Eustice

    University of Michigan, United States

    14 publications · 1K citations

    13

    h-index

  2. PR
    Pere Ridao

    Universitat de Girona, Spain

    8 publications · 559 citations

    8

    h-index

  3. AK
    Ayoung Kim

    Korea Advanced Institute of Science and Technology, South Korea

    7 publications · 584 citations

    7

    h-index

  4. DR
    David Ribas

    Universitat de Girona, Spain

    7 publications · 541 citations

    7

    h-index

  5. SB
    Stefan B. Williams

    The University of Sydney, Australia

    7 publications · 545 citations

    7

    h-index

1–5 of 426

Venues

  1. Autonomous Robots

    10 publications · 723 citations

    10

    h-index

  2. IFAC Proceedings Volumes

    8 publications · 356 citations

    8

    h-index

  3. Journal of Intelligent & Robotic Systems

    5 publications · 76 citations

    5

    h-index

  4. Robotics and Autonomous Systems

    5 publications · 262 citations

    5

    h-index

  5. The International Journal of Robotics Research

    IJRR · 5 publications · 440 citations

    5

    h-index

1–5