Collision Avoidance Under Uncertainty

Collision Avoidance Under Uncertainty is a methodological framework within the domain of collision avoidance that specifically addresses the challenge of preventing collisions in dynamic environments where sensor measurements, state estimates, or environmental conditions are subject to stochasticity, incompleteness, or imprecision.

76

Publications

3.4K

Citations

215

Authors

104

Institutions

Publications per year

2017–2026

33

Authors

215

  1. KK
    Kristian Kroschel

    Karlsruhe Institute of Technology, Germany

    3 publications · 285 citations

    3

    h-index

  2. DG
    Dominique Gruyer

    Université Paris-Sud, France

    2 publications · 146 citations

    2

    h-index

  3. MW
    Mark W. Spong

    University of Illinois Urbana-Champaign, United States

    2 publications · 55 citations

    2

    h-index

  4. JH
    J. Hillenbrand

    Karlsruhe Institute of Technology, Germany

    2 publications · 58 citations

    2

    h-index

  5. WL
    Wenhao Luo

    Carnegie Mellon University, United States

    2 publications · 59 citations

    2

    h-index

1–5 of 215

Venues

  1. arXiv (Cornell University)

    Repository · 4 publications · 299 citations

    4

    h-index

  2. Journal of Navigation

    2 publications · 31 citations

    2

    h-index

  3. Journal of Guidance Control and Dynamics

    2 publications · 137 citations

    2

    h-index

  4. IEEE Transactions on Intelligent Vehicles

    ITIVBL · 2 publications · 79 citations

    2

    h-index

  5. Ocean Engineering

    2 publications · 156 citations

    2

    h-index

1–5