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eBooks
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Autonomous and connected heavy vehicle technology (2022)
For graduate-level students from different engineering disciplines such as automotive and mechanical engineering, computer science, data science and business analytics combines both basic concepts and advanced level content from technical experts.
Online journal articles
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The Road to the Mine of the Future: Autonomous Collaborative Mining (2025)
The automation of mining mobile equipment is a topic of considerable interest, as it has the potential to significantly reduce the number of accidents and implement the so-called zero-entry mining concept, which would eliminate the need for any human presence on the mine site. Nevertheless, the current state of robotics and automation technology does not yet meet the requirements for the implementation of fully autonomous operations in mines. Autonomous mining equipment continues to operate under the supervision of humans, and a considerable number of mining equipment has not yet been automated. This indicates the necessity of identifying novel strategies to increase the safety of mining operations through the utilization of robotics and automation technologies. One potential solution to address this challenge is to increase the involvement of humans in autonomous mining operations. This could entail integrating human decision-makers into the decision-making loops of autonomous mining equipment. To this end, we propose the paradigm of autonomous collaborative mining, wherein humans and autonomous machines work together in a collaborative manner to increase the safety and efficiency of mining operations. We analyze the enabling factors required to implement this paradigm and present the case of autonomous loading using LHDs based on the autonomous collaborative mining paradigm.
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Autonomous mining through cooperative driving and operations enabled by parallel intelligence (2024)
Autonomous mining is promising to address several current issues in the mining sector, such as low productivity, safety concerns, and labor shortages. Although partial automation has been achieved in some mining operations, fully autonomous mining remains challenging due to its complexity and scalability in field environments. Here we propose an autonomous mining framework based on the parallel intelligence methodology, employing self-evolving digital twins to model and guide mining processes in the real world. Our framework features a virtual mining subsystem that learns from simulating real-world scenarios and generates new ones, allowing for low-cost training and testing of the integrated autonomous mining system. Through initial validation and extensive testing, particularly in open-pit mining scenarios, our framework has demonstrated stable and efficient autonomous operations. We’ve since deployed it across more than 30 mines, resulting in the extraction of over 30 million tons of minerals. This implementation effectively eliminates the exposure of human operators to hazardous conditions while ensuring 24-hour uninterrupted operation.
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Autonomous operations reshape open-pit mining (2023)
The article focuses on the increasing popularity of Autonomous Haulage Solutions (AHS) for haul trucks in open-pit mining, highlighting the benefits of enhanced safety, consistent operations, and reduced costs. Topics discussed include the implementation challenges, considerations for automation beyond truck fleets, and the industry's move towards decarbonization through various propulsion methods such as trolleys, battery-electric, hydrogen, or hybrid forms.
Mining & Autonomous Operations News
BHP Billiton
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Which technologies will boost mining safety and productivity?
New uses for technology in the resources industry are regularly being uncovered. While much has been made of automated equipment; artificial intelligence and advanced sensors will also make mining operations more reliable and efficient, as well as help people make better decisions and keep them out of harm’s way.
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The role of digital twins and AI in enhancing decision-making in the mining industry
Generative AI, can be thought of as the next generation of artificial intelligence. It's a form of AI that can create something new by learning from vast amounts of data. Unlike traditional AI, which follows fixed rules to analyse and process information, GenAI can generate insights, predict outcomes and suggest solutions – making decision-making faster, smarter and more adaptive.
