Self-supervised Navigation

Self-Supervised Navigation is a navigational learning framework that acquires spatial understanding and goal-directed movement through internally generated supervisory signals from unlabelled environmental interactions, distinguishing itself from supervised or reinforcement learning approaches by eliminating the need for external annotations or explicit reward functions.

69

Publications

3.5K

Citations

241

Authors

91

Institutions

Publications per year

2017–2026

54

Authors

241

  1. JG
    Jianfeng Gao

    Microsoft Research (United Kingdom), United Kingdom

    5 publications · 867 citations

    5

    h-index

  2. CS
    Cyrill Stachniss

    University of Bonn, Germany

    4 publications · 174 citations

    4

    h-index

  3. DB
    Dhruv Batra

    Georgia Institute of Technology, United States

    3 publications · 87 citations

    3

    h-index

  4. YW
    Yuan-Fang Wang

    University of California, Santa Barbara, United States

    3 publications · 608 citations

    3

    h-index

  5. XL
    Xiaodan Liang

    Sun Yat-sen University, China

    3 publications · 245 citations

    3

    h-index

1–5 of 241

Venues

  1. arXiv (Cornell University)

    Repository · 9 publications · 178 citations

    9

    h-index

  2. IEEE Robotics and Automation Letters

    9 publications · 432 citations

    9

    h-index

  3. 2

    h-index

  4. 2

    h-index

  5. PLoS Computational Biology

    1 publications · 29 citations

    1

    h-index

1–5