Obstacle Detection

Obstacle Detection is a computational perception task within autonomous vehicle systems that identifies and localizes objects or entities in the vehicle’s environment that may impede its intended path, distinguishing it from general scene understanding by focusing specifically on potential physical hazards requiring avoidance.

4.4K

Publications

229.9K

Citations

12.6K

Authors

2.4K

Institutions

Publications per year

2017–2026

1.8K

Authors

12.6K

  1. AB
    Alberto Broggi

    University of Parma, Italy

    32 publications · 3.3K citations

    24

    h-index

  2. LM
    Larry Matthies

    Jet Propulsion Laboratory, United States

    32 publications · 2.1K citations

    23

    h-index

  3. SN
    Sergiu Nedevschi

    Technical University of Cluj-Napoca, Romania

    28 publications · 1.4K citations

    19

    h-index

  4. SS
    Sanjiv Singh

    Carnegie Mellon University, United States

    17 publications · 2.6K citations

    16

    h-index

  5. KY
    Kailun Yang

    Zhejiang University, China

    20 publications · 986 citations

    16

    h-index

1–5 of 12.6K

Venues

  1. 55

    h-index

  2. IEEE Access

    65 publications · 5.5K citations

    39

    h-index

  3. Robotics and Autonomous Systems

    66 publications · 4.3K citations

    38

    h-index

  4. Sensors

    111 publications · 4.8K citations

    38

    h-index

  5. Journal of Field Robotics

    JFR · 36 publications · 6.2K citations

    28

    h-index

1–5