iMAPeM: A New Paradigm for Implementing Intelligent Mining With Humans in the Loop
Yunfeng Ai, Siyu Teng, Qingyuan Yang, Ye Wu, Yuchen Li, Yu Gao, Meng Feng, Shengli Yang, Bin Tian, Long Chen, Fei–Yue Wang
Abstract
Since the 1990s, the automated process within open-pit mines has been rapidly advanced. However, mineral transportation, as the most costly and dangerous production process, has not witnessed efficient achievements. Adverse weather conditions and complex work environments are two critical bottlenecks that impede the development and deployment of autonomous transportation of open-pit mines. To alleviate this issue, this research proposes a novel paradigm, named IMAPeM, designed to enable safe and efficient autonomous transportation with humans in the loop. IMAPeM includes three categories of miners: 1) biological miners; 2) digital miners; and 3) robotic miners, as well as three operational modes: 1) autonomous model (AM); 2) parallel model (PM); and 3) expert/emergency model (EM). IMAPeM employs these miners and modes depend on the complexity of the task, optimizing the utilization of digital and robotic miners while reducing the workload for biological miners. In addition, we developed the YUGONG system based on IMAPeM. The empirical implementation demonstrates the exceptional performance of the YUGONG system in autonomous transportation across diverse open-pit mines. This system contributes to the advancement of sustainable mining practices, which also carries profound significance for achieving long-term environmentally responsible mining operations.