Hybrid Map Representation

Hybrid Map Representation is a type of environment representation that integrates multiple distinct mapping paradigms—such as metric, topological, or semantic representations—into a unified framework, enabling complementary strengths in spatial reasoning, scalability, and interpretability within robotic navigation and geospatial modeling.

39

Publications

1.9K

Citations

104

Authors

61

Institutions

Publications per year

2017–2026

11

Authors

104

  1. JN
    Juan Nieto

    ETH Zurich, Switzerland

    3 publications · 167 citations

    3

    h-index

  2. JL
    Jongwoo Lim

    Hanyang University, South Korea

    2 publications · 69 citations

    2

    h-index

  3. PB
    Patrick Beeson

    The University of Texas at Austin, United States

    2 publications · 216 citations

    2

    h-index

  4. SH
    Sachithra Hemachandra

    Massachusetts Institute of Technology, United States

    2 publications · 79 citations

    2

    h-index

  5. KK
    Kiyosumi Kidono

    Toyota Central Research and Development Laboratories (Japan), Japan

    2 publications · 35 citations

    2

    h-index

1–5 of 104

Venues

  1. The International Journal of Robotics Research

    IJRR · 3 publications · 130 citations

    3

    h-index

  2. Sustainability

    1 publications · 25 citations

    1

    h-index

  3. Data

    1 publications · 50 citations

    1

    h-index

  4. 1

    h-index

  5. GeoInformatica

    1 publications · 11 citations

    1

    h-index

1–5