Graph-based Sensor Fusion

Graph-Based Sensor Fusion is a sensor fusion framework that represents multi-robot perception data and their interdependencies as a graph, where nodes denote sensory measurements or states and edges encode probabilistic constraints or relationships, enabling distributed and scalable state estimation through graph optimization techniques.

34

Publications

1.7K

Citations

133

Authors

48

Institutions

Publications per year

2017–2026

26

Authors

133

  1. BJ
    Bowen Ji

    Nanjing University of Aeronautics and Astronautics, China

    2 publications · 55 citations

    2

    h-index

  2. PL
    Pin Lyu

    Nanjing University of Aeronautics and Astronautics, China

    2 publications · 55 citations

    2

    h-index

  3. SB
    Shiyu Bai

    Nanjing University of Aeronautics and Astronautics, China

    2 publications · 55 citations

    2

    h-index

  4. JL
    Jizhou Lai

    Nanjing University of Aeronautics and Astronautics, China

    2 publications · 55 citations

    2

    h-index

  5. BC
    Bernardo Camajori Tedeschini

    Politecnico di Milano, Italy

    1 publications · 14 citations

    1

    h-index

1–5 of 133

Venues

  1. IEEE Access

    3 publications · 69 citations

    3

    h-index

  2. IEEE Robotics and Automation Letters

    2 publications · 121 citations

    2

    h-index

  3. The International Journal of Robotics Research

    IJRR · 2 publications · 119 citations

    2

    h-index

  4. IEEE Transactions on Industrial Electronics

    2 publications · 111 citations

    2

    h-index

  5. IEEE Transactions on Vehicular Technology

    2 publications · 48 citations

    2

    h-index

1–5