Distance-based Collision Detection

Distance-Based Collision Detection is a collision detection method that determines potential intersections between objects by computing and comparing the minimum distance between their geometric representations against a threshold, distinguishing it from intersection-based or volume-based approaches through its reliance on distance metrics.

80

Publications

6.6K

Citations

202

Authors

84

Institutions

Publications per year

2017–2026

11

Authors

202

  1. ÉG
    Éric Gilbert

    University of Michigan, United States

    4 publications · 1.6K citations

    4

    h-index

  2. DM
    Dinesh Manocha

    University of North Carolina at Chapel Hill, United States

    4 publications · 141 citations

    4

    h-index

  3. SK
    Stefan Kimmerle

    University of Tübingen, Germany

    3 publications · 557 citations

    3

    h-index

  4. AS
    Avneesh Sud

    University of North Carolina at Chapel Hill, United States

    3 publications · 111 citations

    3

    h-index

  5. AF
    Arnulph Fuhrmann

    TH Köln - University of Applied Sciences, Germany

    3 publications · 623 citations

    3

    h-index

1–5 of 202

Venues

  1. ACM Transactions on Graphics

    TOG · 4 publications · 585 citations

    4

    h-index

  2. IEEE Transactions on Robotics

    2 publications · 70 citations

    3

    h-index

  3. IEEE Transactions on Robotics and Automation

    3 publications · 124 citations

    3

    h-index

  4. Robotica

    3 publications · 45 citations

    3

    h-index

  5. Computer Graphics Forum

    2 publications · 519 citations

    2

    h-index

1–5