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市场调查报告书
商品编码
1959930
机器人视觉市场-全球产业规模、份额、趋势、机会、预测:硬体、技术、应用、区域及竞争格局(2021-2031年)Robotic Vision Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, Segmented By Hardware, By Technology, By Application, By Region & Competition, 2021-2031F |
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全球机器人视觉市场预计将从 2025 年的 54.6 亿美元成长到 2031 年的 92.4 亿美元,复合年增长率为 9.16%。
该领域融合了相机硬体和先进的影像处理演算法,使机器人能够在诸如检测、引导和识别等任务中理解并适应环境。其主要成长要素包括对高精度品管日益增长的需求以及缓解製造业严重劳动力短缺的迫切需求。此外,对能够实现大规模客製化的高度适应性生产能力的需求也推动了这些智慧感知系统的应用,使机器人能够在非结构化环境中自主运作。
| 市场概览 | |
|---|---|
| 预测期 | 2027-2031 |
| 市场规模:2025年 | 54.6亿美元 |
| 市场规模:2031年 | 92.4亿美元 |
| 复合年增长率:2026-2031年 | 9.16% |
| 成长最快的细分市场 | 3D视觉 |
| 最大的市场 | 亚太地区 |
然而,大规模市场扩张面临的主要障碍在于实施所需的巨额初始投资以及将这些系统与现有基础设施整合所涉及的技术复杂性。根据国际机器人联合会的数据,到2025年,全球已部署了54.2万台工业机器人。虽然这个数字显示自动化应用规模庞大,但为这些机器人升级先进视觉功能所带来的财务和技术挑战,仍然是许多中小企业面临的主要障碍。
人工智慧 (AI) 和深度学习演算法的融合正在从根本上改变机器人视觉领域。这使得系统能够像人类一样灵活地在复杂且非结构化的环境中导航。与传统的基于规则的程式设计不同,这些以学习为中心的方法使机器能够识别各种物体形状,适应不断变化的光照条件,并在不规则表面上进行品质检测,而无需进行大量的重新编程。这种柔软性对于希望降低自动化僵化程度并适应多品种、小批量生产计划的製造商至关重要。根据罗克韦尔自动化于 2024 年 3 月发布的第九份年度智慧製造情势报告,85% 的受访製造商已投资或计划在 2024 年投资人工智慧和机器学习技术,这凸显了整个产业向这些认知能力的强劲转变。
同时,物流和仓储自动化领域的应用不断扩展,成为推动市场发展的主要动力,这主要源自于加快电子商务订单处理速度的需求。视觉引导机器人正越来越多地应用于动态拣选、分类和堆迭作业中,在这些作业中,识别不同的库存单位(SKU)至关重要。从市场采用统计数据来看,对这些自动化行动解决方案的需求显而易见。国际机器人联合会(IFR)在2024年9月发布的《2024年世界机器人服务机器人报告》中指出,2023年商用销量成长了35%。这项发展动能吸引了许多专注于视觉技术的机器人公司进行大量投资,例如,Figure AI在2024年2月完成了6.75亿美元的B轮资金筹措,旨在加速其通用自主人形机器人的商业化进程。
机器人视觉系统的部署需要大量资金和先进技术,这成为限制市场成长的主要阻碍因素。实现这些先进的感知能力不仅需要购买昂贵的摄影机硬体和处理单元,还需要投入大量成本与现有基础设施整合。这种高进入门槛对中小企业而言尤其严峻,因为它们往往缺乏足够的资金来支付这些初始成本,也缺乏复杂配置所需的专业工程技能。因此,市场难以渗透到对成本敏感的产业,而机器人视觉系统的应用主要限于拥有充足自动化预算的大型製造商。
这些财务压力直接削弱了市场成长势头,尤其是在经济不确定时期,资本支出会受到严格审查。这些经济和技术壁垒的影响也反映在近期行业绩效指标中,这些指标显示需求正在萎缩。根据德国机械设备製造业联合会(VDMA)机器视觉部门的数据,欧洲机器视觉产业预计2024年名目销售额将年减10%。这项放缓凸显了预算限制和整合困难如何迫使製造商推迟投资,阻碍了全球机器人视觉市场的即时成长。
视觉系统与协作机器人的集成,正将自动化能力从基本的取放任务扩展到码垛和焊接等需要动态感知能力的重型作业。与传统的无视觉自动化不同,这些先进的协作机器人利用整合视觉系统来适应不断变化的零件位置和非结构化环境,从而能够处理以前只有大型工业机器人才能完成的复杂工业任务。这种向高性能视觉协作单元的转变正迅速获得市场认可。正如优傲机器人(Universal Robots)在2024年1月发布的《2023年强劲收官》报告中所述,该公司专为视觉密集型应用设计的新型高负载协作机器人UR20和UR30,占第四季度销售额的30%。这显示工业界正朝着灵活、高容量的感知平台方向发生显着转变。
同时,具备嵌入式处理能力的智慧相机的普及正在重塑品质保证策略,因为製造企业正致力于数位转型以提高生产视觉化。市场不再依赖集中式的基于PC的处理,而是转向分散式架构,智慧相机直接在边缘执行侦测演算法,从而显着降低延迟和基础设施复杂性。这一趋势的驱动力源自于企业利用可扩展的视觉资料工具对传统生产线进行现代化改造的策略需求。根据斑马技术公司于2024年6月发布的《2024年製造视觉调查报告》,66%的製造企业领导者计划在未来五年内实施机器视觉解决方案,这凸显了这些嵌入式技术在保护工业运营免受未来质量和劳动力相关挑战方面将发挥的关键作用。
The Global Robotic Vision Market is projected to expand from USD 5.46 Billion in 2025 to USD 9.24 Billion by 2031, reflecting a CAGR of 9.16%. This field encompasses the combination of camera hardware and sophisticated image processing algorithms, allowing robots to interpret and adjust to their environment for duties such as inspection, guidance, and identification. Primary growth drivers include the rising need for high-precision quality control and the necessity to alleviate acute labor shortages within the manufacturing sector. Additionally, the demand for adaptable production capabilities to facilitate mass customization is fueling the uptake of these intelligent perception systems, enabling autonomous robot operation in unstructured settings.
| Market Overview | |
|---|---|
| Forecast Period | 2027-2031 |
| Market Size 2025 | USD 5.46 Billion |
| Market Size 2031 | USD 9.24 Billion |
| CAGR 2026-2031 | 9.16% |
| Fastest Growing Segment | 3D Vision |
| Largest Market | Asia Pacific |
However, widespread market expansion faces significant hurdles due to the heavy initial capital outlay required for deployment and the technical intricacies of merging these systems with existing infrastructure. Data from the International Federation of Robotics indicates that 542,000 industrial robots were installed globally during the year preceding 2025. Although this number highlights the massive scale of automation adoption, the associated financial and technical challenges of upgrading these units with advanced vision capabilities remain a substantial barrier for numerous small and medium-sized enterprises.
Market Driver
The incorporation of artificial intelligence and deep learning algorithms is fundamentally transforming the robotic vision landscape by empowering systems to navigate complex, unstructured environments with adaptability comparable to humans. In contrast to conventional rule-based programming, these learning-centric methods enable machines to identify varying object shapes, adjust for fluctuating lighting, and perform quality inspections on irregular surfaces without significant reprogramming. This flexibility is vital for manufacturers seeking to reduce automation rigidity and handle high-mix production schedules. According to Rockwell Automation's '9th Annual State of Smart Manufacturing Report' from March 2024, 85% of surveyed manufacturers have invested or intend to invest in AI and machine learning technologies in 2024, highlighting a strong industrial shift toward these cognitive capabilities.
Concurrently, the growth of applications within logistics and warehouse automation serves as a major accelerator for the market, spurred by the need to expedite e-commerce order fulfillment. Vision-guided robots are increasingly being utilized for dynamic picking, sorting, and palletizing operations where the identification of various stock-keeping units is crucial. The demand for such automated mobility solutions is evident in deployment statistics; the International Federation of Robotics reported in its 'World Robotics 2024 Service Robots' publication in September 2024 that sales of professional service robots for transportation and logistics surged by 35% in 2023. This momentum is drawing significant investment into vision-focused robotics companies, as demonstrated when Figure AI raised $675 million in Series B funding in February 2024 to speed up the commercial launch of its general-purpose autonomous humanoids.
Market Challenge
Significant financial outlays and the technical sophistication required to deploy robotic vision systems act as substantial constraints on market growth. Implementing these advanced perception abilities necessitates not only purchasing costly camera hardware and processing units but also incurring significant expenses to integrate them with legacy infrastructure. This high entry barrier particularly impacts small and medium-sized enterprises, which frequently lack the financial buffer to handle such upfront costs or the specialized engineering expertise required for complex setups. As a result, the market faces difficulties penetrating cost-sensitive sectors, limiting adoption largely to major manufacturers with substantial automation budgets.
This financial pressure directly reduces market momentum, especially during times of economic uncertainty when capital expenditures undergo rigorous scrutiny. The effect of these economic and technical obstacles is reflected in recent industrial performance metrics, which show a contraction in demand. According to VDMA Machine Vision, the European machine vision sector projected a 10% nominal decrease in sales in 2024 compared to the prior year. This downturn underscores how budget limitations and integration difficulties compel manufacturers to postpone investments, thereby impeding the immediate growth trajectory of the global robotic vision market.
Market Trends
The merging of vision systems with collaborative robots is extending automation capabilities beyond basic pick-and-place tasks into heavy-duty functions necessitating dynamic perception, such as palletizing and welding. Unlike conventional blind automation, these advanced cobots employ integrated vision to adjust to changing part positions and unstructured settings, enabling them to handle complex industrial duties formerly limited to heavy industrial robots. This movement toward high-performance, vision-equipped collaborative units is quickly gaining traction in the market. As noted by Universal Robots in their 'Universal Robots Reports Strong End to 2023' announcement in January 2024, the company's new heavy-payload UR20 and UR30 cobots, engineered for such vision-intensive uses, already represented 30% of fourth-quarter revenue, indicating a clear industrial shift toward flexible, high-capacity perception platforms.
Simultaneously, the widespread adoption of smart cameras featuring embedded processing is reshaping quality assurance strategies as manufacturers focus on digital transformation to improve production visibility. Instead of depending on centralized PC-based processing, the market is shifting toward decentralized architectures where intelligent cameras perform inspection algorithms directly at the edge, which significantly lowers latency and infrastructure complexity. This trend is fueled by a strategic need to update legacy manufacturing lines with scalable visual data tools. According to the '2024 Manufacturing Vision Study' by Zebra Technologies released in June 2024, 66% of manufacturing leaders intend to deploy machine vision solutions within the next five years, highlighting the vital role these embedded technologies play in protecting industrial operations against future quality and labor-related challenges.
Report Scope
In this report, the Global Robotic Vision Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:
Company Profiles: Detailed analysis of the major companies present in the Global Robotic Vision Market.
Global Robotic Vision Market report with the given market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report: