Multi-robot Object Tracking

Multi-Robot Object Tracking is a cooperative perception framework in which multiple robots jointly estimate the trajectories of dynamic objects by fusing sensory observations across space and time, distinguished by its reliance on inter-robot coordination and distributed state estimation to enhance tracking accuracy, continuity, and coverage in complex environments.

24

Publications

851

Citations

71

Authors

34

Institutions

Publications per year

2017–2026

4

Authors

71

  1. PU
    Pedro U. Lima

    Instituto Superior Técnico, Portugal

    3 publications · 74 citations

    3

    h-index

  2. AA
    Aamir Ahmad

    Max Planck Institute for Intelligent Systems, Germany

    3 publications · 74 citations

    3

    h-index

  3. MV
    Manuela Veloso

    Carnegie Mellon University, United States

    3 publications · 96 citations

    3

    h-index

  4. KH
    Kwun Han

    Carnegie Mellon University, United States

    2 publications · 41 citations

    2

    h-index

  5. PS
    Peter Stone

    The University of Texas at Austin, United States

    2 publications · 41 citations

    2

    h-index

1–5 of 71

Venues

  1. Autonomous Robots

    2 publications · 298 citations

    2

    h-index

  2. Robotics and Autonomous Systems

    2 publications · 50 citations

    2

    h-index

  3. Zenodo (CERN European Organization for Nuclear Research)

    Repository · 1 publications · 15 citations

    1

    h-index

  4. Sensors

    1 publications · 20 citations

    1

    h-index

  5. Neurocomputing

    1 publications · 32 citations

    1

    h-index

1–5