Uncertainty Estimation For Avoidance

Uncertainty Estimation for Avoidance is a computational framework within avoidance systems that quantifies epistemic and aleatoric uncertainties to inform risk-aware decision-making by distinguishing between known unknowns and unknown unknowns in safety-critical environments.

4

Publications

186

Citations

9

Authors

6

Institutions

Publications per year

2017–2026

1

Authors

9

  1. LY
    Lee Yang

    Massachusetts Institute of Technology, United States

    3 publications · 164 citations

    2

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  2. JK
    James K. Kuchar

    Massachusetts Institute of Technology, United States

    3 publications · 164 citations

    2

    h-index

  3. SL
    Shixiong Li

    North University of China, China

    1 publications · 19 citations

    1

    h-index

  4. EQ
    Edmond Q. Wu

    Shanghai Jiao Tong University, China

    1 publications · 19 citations

    1

    h-index

  5. SR
    Subramanian Ramasamy

    RMIT University, Australia

    1 publications · 28 citations

    1

    h-index

1–5 of 9

Venues

  1. 1

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  2. Applied Mechanics and Materials

    AMM · 1 publications · 28 citations

    1

    h-index

  3. Journal of Guidance Control and Dynamics

    1 publications · 114 citations

    1

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  4. 35th Aerospace Sciences Meeting and Exhibit

    1 publications · 25 citations

    1

    h-index

1–4