人工智能驱动的仓库自动化:系统综述

Enoch Oluwademilade Sodiya, Uchenna Joseph Umoga, Olukunle Oladipupo Amoo, Akoh Atadoga
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摘要

本综合评论探讨了人工智能(AI)对仓库自动化的深远影响,对各种人工智能驱动的系统进行了深入研究。随着各行各业越来越多地采用自动化来提高效率和简化操作,将人工智能技术整合到仓库管理系统中已变得举足轻重,重塑了物流和供应链管理的格局。人工智能驱动的仓库自动化系统利用先进的算法来优化仓库运营的各个方面,从库存管理到订单执行。机器学习算法在需求预测中发挥着关键作用,使仓库能够预测并适应不断变化的客户需求。计算机视觉技术增强了机器人的视觉能力,促进了物品识别、拾放操作和质量控制等任务。这些进步大大有助于提高仓库流程的准确性、速度和成本效益。本综述详细介绍了人工智能在仓库自动化中的应用,包括自主移动机器人(AMR)、机械臂和自动导引车(AGV)。配备人工智能算法的自动移动机器人可自主导航仓库环境,优化分拣路线并适应仓库布局的变化。通过人工智能增强的机械臂可实现精确和适应性强的物料搬运,提高包装和码垛等任务的效率。由人工智能引导的 AGV 可确保仓库内物料运输的无缝衔接,提高整体运营的灵活性。人工智能驱动的仓库自动化系统的最新趋势凸显了这一领域的动态发展。边缘计算解决方案使这些系统能够在本地处理数据,从而减少延迟并提高实时决策能力。强化学习算法使机器人系统能够根据不断变化的环境条件学习和调整自己的行为,从而促进持续改进和提高效率。总之,本综述阐明了人工智能在改造仓库自动化系统、彻底改变物流和供应链运作方式方面的关键作用。人工智能与仓库自动化之间的协同增效有望推动现代仓库在效率、准确性和适应性方面取得前所未有的进步。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
AI-driven warehouse automation: A comprehensive review of systems
This comprehensive review explores the profound impact of artificial intelligence (AI) on warehouse automation, providing an in-depth examination of various AI-driven systems. As industries increasingly embrace automation to enhance efficiency and streamline operations, the integration of AI technologies into warehouse management systems has become pivotal, reshaping the landscape of logistics and supply chain management. AI-driven warehouse automation systems leverage advanced algorithms to optimize various aspects of warehouse operations, from inventory management to order fulfillment. Machine learning algorithms play a key role in demand forecasting, allowing warehouses to predict and adapt to changing customer needs. Computer vision technologies enhance robotic vision, facilitating tasks such as item recognition, pick-and-place operations, and quality control. These advancements significantly contribute to increased accuracy, speed, and cost-effectiveness in warehouse processes. The review provides a detailed examination of the applications of AI in warehouse automation, encompassing autonomous mobile robots (AMRs), robotic arms, and automated guided vehicles (AGVs). AMRs equipped with AI algorithms navigate warehouse environments autonomously, optimizing pick routes and adapting to changes in the warehouse layout. Robotic arms, enhanced by AI, enable precise and adaptable material handling, contributing to the efficiency of tasks like packing and palletizing. AGVs, guided by AI, ensure seamless material transport within warehouses, enhancing overall operational agility. Recent trends in AI-driven warehouse automation systems underscore the dynamic evolution of this field. Edge computing solutions empower these systems to process data locally, reducing latency and enhancing real-time decision-making. Reinforcement learning algorithms enable robotic systems to learn and adapt their behavior based on changing environmental conditions, contributing to continuous improvement and efficiency gains. In conclusion, this review illuminates the pivotal role of AI in transforming warehouse automation systems, revolutionizing the way logistics and supply chain operations are conducted. The collaborative synergy between AI and warehouse automation promises to drive unprecedented advancements in efficiency, accuracy, and adaptability within the evolving landscape of modern warehouses.
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