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市场调查报告书
商品编码
1876683
自主移动机器人市场预测至2032年:按组件、类型、导航技术、负载容量、应用、最终用户和地区分類的全球分析Autonomous Mobile Robot Market Forecasts to 2032 - Global Analysis By Component, Type, Navigation Technology, Payload Capacity, Application, End User, and By Geography |
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根据 Stratistics MRC 的一项研究,全球自主移动机器人 (AMR) 市场预计到 2025 年将达到 30 亿美元,到 2032 年将达到 102 亿美元。
预计市场在预测期内将以18.7%的复合年增长率成长。自主移动机器人(AMR)是一种具备自主导航能力的智慧机器人,广泛应用于仓库、工厂和医疗机构等场所,用于物料搬运、拣选和检测。与固定式输送机和自动导引车(AGV)不同,AMR能够绘製环境地图、避开障碍物并适应不断变化的工作流程,从而实现快速重新配置并提高效率。随着电子商务需求的成长、劳动力短缺以及对灵活物流的需求,AMR的应用正在不断扩大。扩充性和投资回报率(ROI)取决于吞吐量的提升、部署的便利性以及生态系统的支援。
根据国际机器人联合会 (IFR) 发布的《2023 年世界机器人报告》,2022 年全球商用服务机器人的出货量达到创纪录的 158,000 台。
劳动力短缺日益严重,工资成本不断上涨
推动自主移动机器人(AMR)普及的主要因素是持续且日益严重的劳动力短缺,尤其是在仓储业和製造业领域,以及不断上涨的薪资成本。企业越来越依赖AMR作为维持业务连续性和提高成本可预测性的策略解决方案。这种自动化技术能够持续且有效率地完成物料搬运和拣选等任务,同时降低劳动力波动带来的风险,从而在人手不足的市场环境下直接提高生产力并实现长期营运成本的稳定。
AMR实施和系统整合的初始投资成本很高
自主移动机器人(AMR)广泛应用的一大障碍是其部署所需的高额初始资本投入,包括机器人本身、高级软体整合以及必要的基础设施。对于许多中小企业而言,儘管长期来看可能获得回报,但这笔初始成本仍然是一大阻碍。这项财务门槛要求企业提供令人信服的商业论证来证明投资的合理性,从而延缓了决策流程,并将市场渗透限制在规模更大、资金更雄厚的公司。
开发具备先进人工智慧能力的自主移动机器人(AMR)来处理复杂任务
视觉系统、情境察觉和决策演算法的进步将使机器人能够超越简单的物料搬运任务,执行日益复杂且非重复性的任务。这种发展将拓展自主移动机器人(AMR)的价值提案,使其能够在诸如最终组装和品质检测等动态环境中实现新的应用,从而为尚未开发的工业领域的製造商开闢新的、利润丰厚的收入来源。
互联自主移动机器人系统面临的网路安全风险
随着自主移动机器人(AMR)透过工业物联网(IIoT)实现更紧密的互联,网路安全漏洞带来的威胁也日益加剧。一旦发生安全漏洞,恶意控制机器人可能导致运行中断、资料窃取,甚至引发安全事故。应对此风险需要持续投资于强大的安全通讯协定和加密技术,但这会增加系统复杂性和成本。此外,一次重大安全事件就可能削弱信任,减缓市场成长,使网路安全成为整个产业面临的重大挑战。
新冠疫情极大地推动了自主移动机器人(AMR)市场的发展,暴露了依赖人工的供应链中存在的许多脆弱性,并造成了严重的营运中断。强制性的社交隔离和封锁措施促使企业加速向自动化转型,以确保营运韧性并减少对人力的依赖。这导致对AMR的需求激增,尤其是在电商履约领域,因为企业优先考虑自动化,以建立更具韧性、更能抵御疫情影响的未来营运模式。
预计在预测期内,货物搬运拣货机器人细分市场将占据最大的市场份额。
在电子商务的爆炸性增长和仓库优化迫切需求的推动下,预计在预测期内,拣货机器人细分市场将占据最大的市场份额。货到人拣选显着减少了工人的行走时间,并提高了拣选的准确性和速度,而这些都是履约中心的关键指标。透过将库存直接送到工人手中,这些自主移动机器人(AMR)简化了仓库中最耗费人力的流程,并直接应对了劳动力短缺和消费者对更快订单交付速度日益增长的期望所带来的挑战,使其成为现代物流的基础性投资。
预计混合和多感测器融合领域在预测期内将呈现最高的复合年增长率。
预计在预测期内,混合和多感测器融合领域将实现最高的成长率。这是因为混合系统结合了雷射雷达、视觉系统(在某些情况下还包括声吶)等技术,能够使自主移动机器人(AMR)更加稳健可靠。这种多感测器方法提供冗余数据,从而在动态和人口密集的环境中实现更佳的导航,并能够执行更复杂的任务,例如精确机动。随着应用场景从简单的引导路径发展到更高级的路径导航,对这些感知功能丰富的先进系统的需求正在加速成长,从而推动该领域的显着成长。
在预测期内,北美预计将占据最大的市场份额,这主要得益于主要自主移动机器人(AMR)供应商的强大影响力、高昂的人事费用,以及成熟製造业和大规模电子商务行业对自动化技术的早期积极应用。此外,供应链基础设施现代化方面的大量投资,以及拥有自动化仓库的领先技术公司的存在,共同造就了该地区集中的需求中心。该地区强劲的经济基本面使其能够吸收高额的初始投资,进一步巩固了其在全球AMR市场收入领先地位。
预计亚太地区在预测期内将实现最高的复合年增长率,这主要得益于中国、印度和韩国等国製造业的持续扩张和物流现代化进程。该地区各国政府正积极推动工业4.0奖励,并提供倡议以促进自动化发展。此外,人事费用的上升以及为维持全球出口竞争力而提高生产效率的需求,也是推动自主移动机器人(AMR)技术加速应用的关键因素,为该地区的发展创造了有利条件。
According to Stratistics MRC, the Global Autonomous Mobile Robot (AMR) Market is accounted for $3.0 billion in 2025 and is expected to reach $10.2 billion by 2032, growing at a CAGR of 18.7% during the forecast period. AMRs are intelligent, navigation-capable robots used for material transport, order picking, and inspection in warehouses, factories, and healthcare. Unlike fixed conveyors or AGVs, AMRs map environments, avoid obstacles, and adapt to changing workflows, enabling rapid reconfiguration and efficiency gains. Adoption grows with e-commerce demand, labor shortages, and the need for flexible intralogistics. Scalability and ROI depend on throughput improvement, ease of deployment, and ecosystem support.
According to the International Federation of Robotics (IFR) World Robotics 2023 Report, sales of professional service robots reached a new record of 158,000 units shipped globally in 2022.
Growing labor shortages and rising wage costs
The primary driver for AMR adoption is the persistent and growing labor shortage, particularly in warehousing and manufacturing, coupled with steadily rising wage costs. Companies are increasingly turning to AMRs as a strategic solution to maintain operational continuity and improve cost predictability. This automation mitigates the risk of human resource volatility while ensuring tasks like material transport and picking are completed consistently, directly enhancing productivity and stabilizing long-term operational expenditure in a tight labor market.
High initial investment costs for AMR deployment and system integration
A significant barrier to widespread AMR adoption is the high initial capital expenditure required for deployment, which includes the robots themselves, sophisticated software integration, and necessary infrastructure upgrades. For many small and medium-sized enterprises, this upfront cost can be prohibitive, despite the promise of long-term ROI. This financial hurdle necessitates a compelling business case to justify the investment, often slowing down the decision-making process and limiting market penetration to larger, more capital-rich organizations.
Development of AMRs with enhanced AI capabilities for complex tasks
Enhancements in vision systems, contextual awareness, and decision-making algorithms will allow robots to perform increasingly complex and non-repetitive tasks beyond simple transport. This evolution will unlock new applications in dynamic environments like final assembly or quality inspection, thereby expanding the AMR's value proposition and opening up new, high-margin revenue streams for manufacturers in untapped industry verticals.
Cybersecurity risks in connected AMR systems
As AMRs become more connected through the Industrial Internet of Things (IIoT), they face an escalating threat from cybersecurity vulnerabilities. A breach could lead to operational shutdown, data theft, or even safety incidents if robots are maliciously controlled. This risk necessitates continuous investment in robust security protocols and encryption, which can increase system complexity and cost. Moreover, a single high-profile security incident could erode trust and slow market growth, making cybersecurity a critical challenge for the entire industry.
The COVID-19 pandemic acted as a significant catalyst for the AMR market. It exposed critical vulnerabilities in supply chains reliant on manual labor, causing severe disruptions. The enforced social distancing protocols and lockdowns accelerated the shift towards automation as companies sought to ensure operational resilience and reduce human dependency. This led to a surge in demand for AMRs, particularly in e-commerce fulfillment and logistics, as businesses prioritized automation to build more robust and pandemic-proof operations for the future.
The goods-to-person picking robots segment is expected to be the largest during the forecast period
The goods-to-person picking robots segment is expected to account for the largest market share during the forecast period, which is attributed to the explosive growth of e-commerce and the pressing need for warehouse optimization. Goods-to-person systems drastically reduce operator walking time and increase picking accuracy and speed, which are critical metrics in fulfillment centers. By bringing inventory directly to workers, these AMRs streamline the most labor-intensive process in a warehouse, directly addressing the challenges of labor shortages and rising consumer expectations for rapid order delivery, making them a foundational investment for modern logistics.
The hybrid and multi-sensor fusion segment is expected to have the highest CAGR during the forecast period
Over the forecast period, the hybrid and multi-sensor fusion segment is predicted to witness the highest growth rate because hybrid systems, which combine technologies like LiDAR with vision systems and sometimes sonar, create a more robust and reliable AMR. This multi-sensor approach provides redundant data, allowing for superior navigation in dynamic, human-populated environments and enabling more complex tasks like precise manipulation. As applications move beyond simple guided paths, the demand for these advanced, perception-rich systems is accelerating, driving significant growth in this segment.
During the forecast period, the North America region is expected to hold the largest market share, fueled by a strong presence of major AMR vendors, high labor costs, and an early, aggressive adoption of automation technologies across its mature manufacturing and massive e-commerce sectors. Furthermore, substantial investments in modernizing supply chain infrastructure and the presence of tech giants with automated warehouses create a concentrated hub of demand. The region's robust economic capacity to absorb high initial investments further consolidates its position as the current revenue leader in the global AMR market.
Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR, driven by the relentless expansion of its manufacturing sector and the ongoing logistics modernization in countries like China, India, and South Korea. Governments in the region are actively promoting Industry 4.0 initiatives, incentivizing automation. Additionally, rising labor costs and the need to improve production efficiency to maintain a competitive edge in global exports are compelling factors creating a fertile ground for the accelerated adoption of AMR technologies.
Key players in the market
Some of the key players in Autonomous Mobile Robot Market include Mobile Industrial Robots A/S, Locus Robotics, Inc., Geek+ Technology Co., Ltd., OTTO Motors, Seegrid Corporation, GreyOrange Pte. Ltd., Hai Robotics Co., Ltd., Amazon Robotics, Inc., Swisslog Holding AG, Dematic GmbH, Zebra Technologies Corporation, KUKA Aktiengesellschaft, ABB Ltd., OMRON Corporation, Boston Dynamics, Inc., Clearpath Robotics, Inc., FANUC Corporation, Yaskawa Electric Corporation, IAM Robotics, Inc., and inVia Robotics, Inc.
In June 2025, Seegrid announced its AMRs surpassed 17 million autonomous miles and continues to post product launches and leadership appointments on its news hub.
In April 2025, Boston Dynamics expanded collaboration with Hyundai Motor Group to scale manufacturing and published program updates and partner MOUs on its official news page.
In November 2024, MiR announced the launch of the MiR MC600, a mobile collaborative robot (cobot) that combines a MiR600 autonomous mobile robot base with Universal Robots' heavy-payload UR20/UR30 collaborative robot arms. The MC600 can handle payloads up to 600 kg and is designed for complex industrial workflows such as palletizing, box handling, and machine tending.
Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.