Quality Measure Optimization

Quality Measure Optimization is a methodological framework within grasp quality assessment that systematically enhances the evaluation of robotic grasp stability and effectiveness by refining the mathematical and computational criteria used to quantify grasp performance.

71

Publications

4.7K

Citations

213

Authors

106

Institutions

Publications per year

2017–2026

10

Authors

213

  1. GA
    Ghassan AlRegib

    Georgia Institute of Technology, United States

    2 publications · 56 citations

    2

    h-index

  2. BK
    Barbara Kitchenham

    Keele University, United Kingdom

    2 publications · 39 citations

    2

    h-index

  3. UT
    Uri Tasch

    University of Maryland, Baltimore County, United States

    2 publications · 31 citations

    2

    h-index

  4. DW
    Dorothea Wagner

    Karlsruhe Institute of Technology, Germany

    2 publications · 1.3K citations

    2

    h-index

  5. DL
    Douglas L. Jones

    University of Illinois Urbana-Champaign, United States

    2 publications · 107 citations

    2

    h-index

1–5 of 213

Venues

  1. The International Journal of Robotics Research

    IJRR · 2 publications · 112 citations

    2

    h-index

  2. 2

    h-index

  3. 2

    h-index

  4. IEEE Transactions on Computers

    2 publications · 80 citations

    2

    h-index

  5. IEE Proceedings - Radar Sonar and Navigation

    1 publications · 69 citations

    1

    h-index

1–5