Parallel Mining Operating Systems: From Digital Twins to Mining Intelligence

With the rapid development and modernization requirement of global coal industry, there is an emerging need for intelligent and unmanned mining systems. In this paper, the Intelligent Mining Operating System (IMOS) is proposed and developed, based on the parallel management and control of mining operating infrastructure that integrates the intelligent mining theory, the ACP-based (Artificial societies, Computational experiments, Parallel execution) parallel intelligence approaches, and the new generation of artificial intelligence (AI) technologies. To satisfy the intelligent and unmanned demand of open-pit mines, the IMOS architecture is developed by integrating the theory of digital quadruplets. The main subsystems and functions of IMOS are elaborated in detail, including a single-vehicle operating subsystem, multi-vehicle collaboration subsystem, vehicle-road collaboration subsystem, unmanned intelligent subsystem, dispatch management subsystem, parallel management and control subsystem, supervisory subsystem, remote takeover subsystem, and communication subsystem. The IMOS presented in this paper is the first integrated solution for intelligent and unmanned mines in China, and has been implemented over ten main open pits in the past few years. Its deployment and utilization will effectively improve the production efficiency and safety level of open-pit mines, promote the construction of ecological mines, and bring great significance to the realization of sustainable mining development

Modeling, estimation, and control of robot-soil interactions

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2001.Includes bibliographical references (p. 257-267).This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.This thesis presents the development of hardware, theory, and experimental methods to enable a robotic manipulator arm to interact with soils and estimate soil properties from interaction forces. Unlike the majority of robotic systems interacting with soil, our objective is parameter estimation, not excavation. To this end, we design our manipulator with a flat plate for easy modeling of interactions. By using a flat plate, we take advantage of the wealth of research on the similar problem of earth pressure on retaining walls. There are a number of existing earth pressure models. These models typically provide estimates of force which are in uncertain relation to the true force. A recent technique, known as numerical limit analysis, provides upper and lower bounds on the true force. Predictions from the numerical limit analysis technique are shown to be in good agreement with other accepted models. Experimental methods for plate insertion, soil-tool interface friction estimation, and control of applied forces on the soil are presented. In addition, a novel graphical technique for inverting the soil models is developed, which is an improvement over standard nonlinear optimization. This graphical technique utilizes the uncertainties associated with each set of force measurements to obtain all possible parameters which could have produced the measured forces.(cont.) The system is tested on three cohesionless soils, two in a loose state and one in a loose and dense state. The results are compared with friction angles obtained from direct shear tests. The results highlight a number of key points. Common assumptions are made in soil modeling. Most notably, the Mohr-Coulomb failure law and perfectly plastic behavior. In the direct shear tests, a marked dependence of friction angle on the normal stress at low stresses is found. This has ramifications for any study of friction done at low stresses. In addition, gradual failures are often observed for vertical tools and tools inclined away from the direction of motion. After accounting for the change in friction angle at low stresses, the results show good agreement with the direct shear values.by Won Hong.Ph.D