Uncertainty-aware Planning

Uncertainty-Aware Planning is a navigation planning approach that systematically incorporates quantified uncertainty in environmental dynamics, sensor measurements, or action outcomes to generate robust and adaptive trajectories under imperfect information.

301

Publications

23.6K

Citations

741

Authors

278

Institutions

Publications per year

2017–2026

76

Authors

741

  1. JP
    Jonathan P. How

    Massachusetts Institute of Technology, United States

    7 publications · 333 citations

    7

    h-index

  2. GS
    Gaurav S. Sukhatme

    University of Southern California, United States

    6 publications · 273 citations

    6

    h-index

  3. DE
    David E. Smith

    Ames Research Center, United States

    6 publications · 676 citations

    6

    h-index

  4. RD
    Richard Dearden

    University of Birmingham, United Kingdom

    5 publications · 294 citations

    5

    h-index

  5. BR
    Bruce R. Donald

    Duke University, United States

    4 publications · 194 citations

    4

    h-index

1–5 of 741

Venues

  1. The International Journal of Robotics Research

    IJRR · 8 publications · 929 citations

    8

    h-index

  2. arXiv (Cornell University)

    Repository · 7 publications · 335 citations

    7

    h-index

  3. IEEE Robotics and Automation Letters

    6 publications · 235 citations

    6

    h-index

  4. Autonomous Robots

    5 publications · 369 citations

    5

    h-index

  5. Artificial Intelligence

    5 publications · 312 citations

    5

    h-index

1–5