Asymptotic Properties

Asymptotic Properties is a theoretical construct in probabilistic roadmap methods that characterizes the convergence behavior of sampling-based motion planning algorithms as the number of samples approaches infinity.

8.2K

Publications

496.9K

Citations

12.3K

Authors

3.1K

Institutions

Publications per year

2017–2026

1.2K

Authors

12.3K

  1. GY
    George Yin

    Wayne State University, United States

    17 publications · 1.3K citations

    16

    h-index

  2. PS
    Petre Stoica

    Uppsala University, Sweden

    19 publications · 2.3K citations

    15

    h-index

  3. RE
    Rudolph E. Langer

    University of Wisconsin–Madison, United States

    16 publications · 949 citations

    15

    h-index

  4. PK
    Pranab Kumar Sen

    University of North Carolina at Chapel Hill, United States

    20 publications · 725 citations

    14

    h-index

  5. HD
    Holger Dette

    Ruhr University Bochum, Germany

    16 publications · 908 citations

    14

    h-index

1–5 of 12.3K

Venues

  1. The Annals of Statistics

    306 publications · 37.7K citations

    96

    h-index

  2. Journal of the American Statistical Association

    321 publications · 37.6K citations

    88

    h-index

  3. Biometrika

    141 publications · 12.2K citations

    53

    h-index

  4. IEEE Transactions on Information Theory

    135 publications · 10.7K citations

    51

    h-index

  5. Econometrica

    62 publications · 24.9K citations

    51

    h-index

1–5