Industrial Progress of Robotic Automation in Mining Applications: A Survey
Abstract With the continuous innovations in cutting-edge engineering sciences, advancements in robotic autonomous systems (RAS) have opened up new possibilities in the mining sector, showing promise in replacing humans for various tasks. While RAS has been playing a pivotal role in developing intelligent mining machines, a timely and thorough survey of these applications is still lacking. This paper aims to bridge this gap by chronologically exploring the industrial progress of conventional mobile robotic platforms in mining, such as drilling rig, impact hammer, earthmoving equipment, and haulage truck. The review primarily highlights the real-world industrial implementations in mining automation rather than delving deeply into technological and methodological developments. Given that every robotic autonomous mining system (RAMS) must be thoroughly evaluated during the design phase before deployment in the real world, we furthermore perform a comprehensive review of performance evaluation methods pertinent to the design of RAMSs from both the individual level and overall system level. The paper concludes with an overview of future research and development trends in this evolving field.
Authors
- Jun Tong
- Linping Chan (ORCID: https://orcid.org/0000-0002-1458-4217)
- Christian Ritz (ORCID: https://orcid.org/0000-0002-5095-0624)
- Qinghua Guo (ORCID: https://orcid.org/0000-0002-1065-0838)
- Yanguang Yu (ORCID: https://orcid.org/0000-0002-1541-9061)
- Haiping Du (ORCID: https://orcid.org/0000-0002-3439-3821)
- Faisel Tubbal (ORCID: https://orcid.org/0000-0002-7561-9903)
- Zheng Li (ORCID: https://orcid.org/0000-0002-2734-9419)
- Montserrat Ros (ORCID: https://orcid.org/0000-0002-5598-7987)
- Md. Rabiul Islam (ORCID: https://orcid.org/0000-0003-2820-3144)
- Fazel Naghdy (ORCID: https://orcid.org/0000-0002-9065-3181)
- Raad Raad (ORCID: https://orcid.org/0000-0002-2347-4837)
Institutions
- University of Wollongong (AU)
Publication Details
- Journal
- Mining Metallurgy & Exploration
- Published
- 2025-03-04
- DOI
- https://doi.org/10.1007/s42461-025-01219-y
- Citations
- 11
- Primary Topic
- Advanced Manufacturing and Logistics Optimization
- Type
- article
- Field-Weighted Citation Impact
- 13.67
Funders
- University of Wollongong