Robot Perception

Robot perception is a computational process through which an autonomous system interprets multisensory environmental data to construct spatial and semantic representations enabling informed autonomous decision-making and action.

4.4K

Publications

298.8K

Citations

11.4K

Authors

1.9K

Institutions

Publications per year

2017–2026

1.8K

Authors

11.4K

  1. WB
    Wolfram Burgard

    University of Freiburg, Germany

    56 publications · 15K citations

    35

    h-index

  2. RS
    Roland Siegwart

    ETH Zurich, Switzerland

    46 publications · 3.5K citations

    29

    h-index

  3. CS
    Cyrill Stachniss

    University of Bonn, Germany

    33 publications · 7.3K citations

    26

    h-index

  4. JJ
    John J. Leonard

    Massachusetts Institute of Technology, United States

    27 publications · 6.4K citations

    22

    h-index

  5. HI
    Henrik I. Christensen

    KTH Royal Institute of Technology, Sweden

    22 publications · 1.2K citations

    20

    h-index

1–5 of 11.4K

Venues

  1. IEEE Robotics and Automation Letters

    130 publications · 7.7K citations

    50

    h-index

  2. The International Journal of Robotics Research

    IJRR · 88 publications · 12.1K citations

    47

    h-index

  3. Robotics and Autonomous Systems

    123 publications · 9K citations

    45

    h-index

  4. IEEE Transactions on Robotics

    67 publications · 17.3K citations

    42

    h-index

  5. Journal of Field Robotics

    JFR · 50 publications · 3.9K citations

    33

    h-index

1–5

See also

Robot Perception

Core Methods

Sensor Modalities

Representations

Evaluation

Applications