Joven Tan, Noune Melkoumian, David Harvey, Rini Akmeliawati
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引用次数: 0
摘要
环境挑战、高安全风险和运营效率低下是采矿业面临的一些问题。本文通过将蜂群机器人技术、自然启发算法(NIAs)和其他基于仿生学的技术结合到一个框架中,提出了解决这些问题的综合观点。报告对每种方法进行了系统分类,强调了它们的主要优缺点,并考虑了实际采矿应用场景,包括危险探测、自主运输和节能钻探。本文还引用案例研究来展示这些方法如何协同工作,并通过一个广泛的比较表来考虑这些方法在 Boliden、Diavik Diamond Mine、Olympic Dam 等矿山的应用,从而总结出这些方法的可扩展性和实用性。本文强调了未来的发展方向,如多机器人协调和混合 NIA,以提高操作弹性和可持续性。本文还概述了仿生学,并对实时适应、参数调整和机械磨损等尚未解决的问题进行了批判性研究。本文旨在全面介绍如何利用生物启发模型提高采矿效率、安全性和环境管理,同时提出一个路线图,以解决采矿业广泛采用这些技术仍面临的障碍。
Nature-Inspired Solutions for Sustainable Mining: Applications of NIAs, Swarm Robotics, and Other Biomimicry-Based Technologies.
Environmental challenges, high safety risks and operational inefficiencies are some of the issues facing the mining sector. The paper offers an integrated viewpoint to address these issues by combining swarm robotics, nature-inspired algorithms (NIAs) and other biomimicry-based technologies into a single framework. It presents a systematic classification of each methodology, emphasizing their key advantages and disadvantages as well as considering real-life mining application scenarios, including hazard detection, autonomous transportation and energy-efficient drilling. Case studies are citied to demonstrate how these methodologies work together, and an extensive comparison table considering their applications at mines, such as Boliden, Diavik Diamond Mine, Olympic Dam and others, presents a summary of their scalability and practicality. This paper highlights future directions such as multi-robot coordination and hybrid NIAs, to improve operational resilience and sustainability. It also provides a broad overview of biomimicry and critically examines unresolved issues like real-time adaptation, parameter tuning and mechanical wear. The paper aims to offer a comprehensive insight into using bio-inspired models to enhance mining efficiency, safety and environmental management, while proposing a road map for resolving the issues that continue to be a hurdle for wide adaptation of these technologies in the mining industry.