Autonomous Mining Perception

Autonomous Mining Perception is a computational framework that enables unmanned mining systems to interpret and understand their operational environment through sensor-driven data analysis, distinguishing itself by integrating real-time geological and mechanical contextual awareness into decision-making processes for navigation, obstacle avoidance, and resource identification in unstructured underground and surface mining conditions.

14

Publications

410

Citations

67

Authors

27

Institutions

Publications per year

2017–2026

10

Authors

67

  1. YA
    Yunfeng Ai

    University of Chinese Academy of Sciences, China

    2 publications · 122 citations

    2

    h-index

  2. BT
    Bin Tian

    Chinese Academy of Sciences, China

    2 publications · 122 citations

    2

    h-index

  3. LC
    Long Chen

    Sun Yat-sen University, China

    2 publications · 122 citations

    2

    h-index

  4. DC
    Dongpu Cao

    University of Waterloo, Canada

    2 publications · 122 citations

    2

    h-index

  5. JG
    Jeremy Green

    Johannes Gutenberg University Mainz, Germany

    1 publications · 11 citations

    1

    h-index

1–5 of 67

Venues

  1. Mining Metallurgy & Exploration

    MME · 2 publications · 39 citations

    2

    h-index

  2. Computer Vision and Pattern Recognition

    Conference · 1 publications · 21 citations

    1

    h-index

  3. 1

    h-index

  4. Information Fusion

    1 publications · 28 citations

    1

    h-index

  5. 1

    h-index

1–5