Multi-agent Rapidly Exploring Random Trees

Multi-Agent Rapidly Exploring Random Trees is a path planning framework that extends the Rapidly Exploring Random Trees algorithm by enabling coordinated exploration and motion planning of multiple agents through shared configuration space sampling and inter-agent collision avoidance constraints.

13

Publications

803

Citations

39

Authors

19

Institutions

Publications per year

2017–2026

5

Variants

Marrt

Authors

39

  1. JP
    Jonathan P. How

    Massachusetts Institute of Technology, United States

    3 publications · 169 citations

    3

    h-index

  2. BL
    Brandon Luders

    Massachusetts Institute of Technology, United States

    2 publications · 93 citations

    2

    h-index

  3. DS
    Daniel S. Levine

    University of California, Berkeley, United States

    2 publications · 93 citations

    2

    h-index

  4. VK
    Vijay Kumar

    University of Pennsylvania, United States

    2 publications · 63 citations

    2

    h-index

  5. JM
    Joel M. Esposito

    United States Naval Academy, United States

    2 publications · 63 citations

    2

    h-index

1–5 of 39

Venues

  1. The International Journal of Robotics Research

    IJRR · 1 publications · 21 citations

    1

    h-index

  2. Journal of Aerospace Information Systems

    JAIS · 1 publications · 24 citations

    1

    h-index

  3. Journal of Intelligent & Robotic Systems

    1 publications · 22 citations

    1

    h-index

  4. International Journal of Advanced Robotic Systems

    ARS · 1 publications · 32 citations

    1

    h-index

  5. AIAA Infotech@Aerospace 2010

    1 publications · 69 citations

    1

    h-index

1–5