Dynamic Obstacle Tracking

Dynamic Obstacle Tracking is a computational method within autonomous navigation that enables the continuous estimation and prediction of the motion states of moving obstacles in real-time to support safe and adaptive path planning.

19

Publications

582

Citations

49

Authors

24

Institutions

Publications per year

2017–2026

10

Authors

49

  1. MC
    Mark Campbell

    Cornell University, United States

    3 publications · 116 citations

    3

    h-index

  2. XZ
    Xiaoyang Zhan

    Carnegie Mellon University, United States

    2 publications · 93 citations

    2

    h-index

  3. PR
    P R Jayasree

    Amrita Vishwa Vidyapeetham, India

    2 publications · 33 citations

    2

    h-index

  4. RD
    Radu Dănescu

    Technical University of Cluj-Napoca, Romania

    2 publications · 37 citations

    2

    h-index

  5. KS
    Kenji Shimada

    Carnegie Mellon University, United States

    2 publications · 93 citations

    2

    h-index

1–5 of 49

Venues

  1. IEEE Transactions on Robotics

    3 publications · 133 citations

    3

    h-index

  2. 2

    h-index

  3. 1

    h-index

  4. 1

    h-index

  5. ICT Express

    1 publications · 34 citations

    1

    h-index

1–5