Learning-based Navigation

Learning-Based Navigation is a navigation paradigm within autonomous field navigation that employs machine learning models to acquire navigational policies or behaviors from data, distinguishing itself from traditional rule-based or metric-centric approaches by enabling adaptive decision-making through experience-driven learning.

120

Publications

5K

Citations

408

Authors

145

Institutions

Publications per year

2017–2026

64

Authors

408

  1. PS
    Peter Stone

    The University of Texas at Austin, United States

    4 publications · 411 citations

    4

    h-index

  2. XX
    Xuesu Xiao

    The University of Texas at Austin, United States

    4 publications · 411 citations

    4

    h-index

  3. BL
    Bo Liu

    The University of Texas at Austin, United States

    4 publications · 411 citations

    4

    h-index

  4. JL
    Jens Lambrecht

    Technische Universität Berlin, Germany

    3 publications · 114 citations

    3

    h-index

  5. VJ
    Vijay Janapa Reddi

    Harvard University Press, United States

    3 publications · 68 citations

    3

    h-index

1–5 of 408

Venues

  1. arXiv (Cornell University)

    Repository · 6 publications · 164 citations

    6

    h-index

  2. IEEE Robotics and Automation Letters

    5 publications · 267 citations

    5

    h-index

  3. Journal of Field Robotics

    JFR · 4 publications · 250 citations

    4

    h-index

  4. Autonomous Robots

    3 publications · 441 citations

    3

    h-index

  5. IEEE Access

    3 publications · 286 citations

    3

    h-index

1–5