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
Parents
14
A campaign in autonomous mine mapping
Christopher Baker, Aaron Morris, Dave Ferguson et al. · 2004 · 68 citations
Parallel End-to-End Autonomous Mining: An IoT-Oriented Approach
Yu Gao, Yunfeng Ai, Bin Tian et al. · IEEE Internet of Things Journal · 2019 · 60 citations
1–5 of 14
67
2
h-index
2
h-index
2
h-index
2
h-index
1
h-index
1–5 of 67
27

Chinese Academy of Sciences
Beijing, China
2 h-index
3 publications
182 citations

Sun Yat-sen University
Guangzhou, China
2 h-index
2 publications
122 citations
University of Chinese Academy of Sciences
Beijing, China
2 h-index
2 publications
122 citations
Beijing Academy of Artificial Intelligence
Beijing, China
1 h-index
1 publications
60 citations
Barrick Gold (Canada)
Toronto, Canada
1 h-index
2 publications
22 citations

Universitat de Girona
Girona, Spain
1 h-index
3 publications
42 citations

University of Genoa
Genoa, Italy
1 h-index
3 publications
42 citations
Jilin Province Science and Technology Department
Changchun, China
1 h-index
1 publications
60 citations
1–8 of 27
MME · 2 publications · 39 citations
2
h-index
Conference · 1 publications · 21 citations
1
h-index
Conference · 1 publications · 62 citations
1
h-index
1 publications · 28 citations
1
h-index
1 publications · 14 citations
1
h-index
1–5