Distributed Motion Planning

Distributed Motion Planning is a multi-robot navigation framework in which individual robots compute their trajectories autonomously while exchanging limited, local information with neighboring agents to achieve global collision-free coordination without centralized oversight.

237

Publications

14.4K

Citations

609

Authors

261

Institutions

Publications per year

2017–2026

71

Variants

Decentralized Motion Planning

Authors

609

  1. MM
    Michael M. Zavlanos

    Duke University, United States

    7 publications · 402 citations

    7

    h-index

  2. DR
    Daniela Rus

    Massachusetts Institute of Technology, United States

    7 publications · 425 citations

    7

    h-index

  3. VK
    Vijay Kumar

    University of Pennsylvania, United States

    7 publications · 315 citations

    7

    h-index

  4. DV
    Dimos V. Dimarogonas

    KTH Royal Institute of Technology, Sweden

    6 publications · 367 citations

    6

    h-index

  5. JA
    Javier Alonso–Mora

    Delft University of Technology, Netherlands

    5 publications · 548 citations

    5

    h-index

1–5 of 609

Venues

  1. IEEE Transactions on Robotics

    9 publications · 629 citations

    9

    h-index

  2. Robotics and Autonomous Systems

    7 publications · 416 citations

    7

    h-index

  3. IEEE Robotics and Automation Letters

    8 publications · 903 citations

    7

    h-index

  4. Journal of Intelligent & Robotic Systems

    6 publications · 155 citations

    6

    h-index

  5. The International Journal of Robotics Research

    IJRR · 6 publications · 1.4K citations

    6

    h-index

1–5