Multi-agent Path Planning

Multi-Agent Path Planning is a computational framework within multi-robot scheduling that determines collision-free trajectories for multiple autonomous agents by coordinating their movements from initial positions to designated goals while optimizing path efficiency and respecting spatial and temporal constraints.

579

Publications

32.5K

Citations

1.4K

Authors

454

Institutions

Publications per year

2017–2026

320

Variants

Mapp

Authors

1.4K

  1. SK
    Sven Koenig

    University of Southern California, United States

    56 publications · 3.6K citations

    34

    h-index

  2. HM
    Hang Ma

    University of Southern California, United States

    35 publications · 2.7K citations

    29

    h-index

  3. JL
    Jiaoyang Li

    University of Southern California, United States

    32 publications · 2.2K citations

    24

    h-index

  4. AF
    Ariel Felner

    Ben-Gurion University of the Negev, Israel

    26 publications · 3.3K citations

    22

    h-index

  5. RS
    Roni Stern

    Ben-Gurion University of the Negev, Israel

    24 publications · 3.1K citations

    21

    h-index

1–5 of 1.4K

Venues

  1. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 24 publications · 2.2K citations

    20

    h-index

  2. IEEE Robotics and Automation Letters

    22 publications · 1.4K citations

    20

    h-index

  3. 17

    h-index

  4. arXiv (Cornell University)

    Repository · 23 publications · 885 citations

    16

    h-index

  5. 14

    h-index

1–5