Map Merging

Map Merging is a method in multi-robot perception that combines spatially consistent environmental representations from multiple robots into a single unified map by aligning and integrating their local observations and coordinate frames.

114

Publications

5K

Citations

331

Authors

132

Institutions

Publications per year

2017–2026

41

Authors

331

  1. HL
    Howard Li

    University of New Brunswick, Canada

    5 publications · 162 citations

    5

    h-index

  2. LP
    Liam Paull

    Université de Montréal, Canada

    5 publications · 162 citations

    5

    h-index

  3. SS
    Sajad Saeedi

    Imperial College London, United Kingdom

    5 publications · 162 citations

    5

    h-index

  4. JE
    Jack E. Staub

    University of Wisconsin–Madison, United States

    5 publications · 173 citations

    5

    h-index

  5. MT
    Michael Trentini

    Defence Research and Development Canada, Canada

    5 publications · 162 citations

    5

    h-index

1–5 of 331

Venues

  1. Advanced Robotics

    4 publications · 87 citations

    4

    h-index

  2. IEEE Robotics and Automation Letters

    4 publications · 360 citations

    4

    h-index

  3. Genome

    3 publications · 150 citations

    3

    h-index

  4. Autonomous Robots

    3 publications · 192 citations

    3

    h-index

  5. Electronics

    3 publications · 44 citations

    3

    h-index

1–5