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市场调查报告书
商品编码
1860059
云端机器人:全球市场份额和排名、总销售额和需求预测(2025-2031 年)Cloud Robotics - Global Market Share and Ranking, Overall Sales and Demand Forecast 2025-2031 |
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全球云端机器人市场预计在 2024 年达到 8.52 亿美元,预计到 2031 年将达到 19.73 亿美元,在预测期(2025-2031 年)内以 12.5% 的复合年增长率增长。
云端机器人技术是机器人领域的新兴分支,它基于云端运算、云端储存和其他互联网技术,充分利用整合基础设施和共用服务的优势。这使得机器人能够利用现代资料中心提供的强大运算、储存和通讯资源,同时降低维护和更新的成本以及对客製化中间件的依赖。
市场主要驱动因素包括:
技术创新推动功能边界的扩展
云端机器人透过「云端大脑+边缘执行」架构实现了运算能力与成本之间的平衡。这得归功于技术的突破。一方面,5G网路的广泛应用和边缘运算能力的提升,使得机器人能够即时撷取资料并以低延迟做出决策。例如,远端手术机器人借助云端基础人工智慧的辅助,实现了毫米的手术精确度。另一方面,多模态感知技术(例如3D视觉和触觉感测器)与轻量级模型的融合,提高了机器人的环境适应能力。例如,工业检测机器人能够自主识别设备故障并产生维修方案。此外,大规模人工智慧模型与机器人控制系统的深度融合,正在推动机器人从「程式执行」到「认知自主」的演进。例如,服务机器人利用自然语言处理技术来理解使用者需求,并动态调整服务流程。
应用场景多样化推动市场需求爆炸性成长
云端机器人技术已从单一工业场景扩展到许多领域,形成了一个庞大的应用生态系统。在工业製造领域,对灵活生产的需求正在推动机器人集群的协同作业。例如,在汽车焊接工厂,云端基础的调度能够为多台机器人进行动态路径规划,从而提高生产效率。在医疗领域,远距手术和復健护理正变得至关重要。例如,整形外科手术机器人利用5G和云端运算技术,实现远端专家的即时指导。在紧急救援中,云端机器人可以取代人类在危险环境中工作,利用自主导航和影像识别技术在地震废墟中搜寻倖存者。此外,智慧升级正在拓展家庭服务和物流仓储等领域的市场。例如,清洁机器人可以透过云端更新清洁演算法,以适应每个家庭的需求。
政策支持和产业合作是发展的基础。
在全球范围内,智慧製造和机器人产业的战略升级为云端机器人技术带来了政策利好。中国的「十四五」规划将机器人产业列为重点发展领域,并透过补贴和试验计画加速技术应用。德国的「工业4.0」计画推动製造业数位化,鼓励企业采用具备云端连接的智慧型设备。美国国家机器人倡议支持医疗、国防等关键领域核心云机器人技术的研究与开发。同时,全产业链的协同创新正在降低云端机器人技术的应用门槛:半导体公司推出低功耗人工智慧运算模组,通讯公司优化5G专网解决方案,软体公司开发标准化云端平台,共同建构「硬体、连接和演算法」的封闭生态系统。例如,当虹科技的超低延迟远端控制系统利用多模态压缩和全球通讯技术消除了偏远地区的讯号盲区,促进了云端机器人技术在电力巡检等场景中的广泛应用。
本报告旨在按地区/国家、类型和应用对全球云端机器人市场进行全面分析,重点关注总收入、市场份额和主要企业的排名。
本报告以销售收入为指标,对云端机器人市场规模、估算和预测进行了呈现,以 2024 年为基准年,并包含了 2020 年至 2031 年的历史数据和预测数据。报告运用定量和定性分析,帮助读者制定云端机器人业务/成长策略,评估竞争格局,分析自身在当前市场中的地位,并做出明智的商业决策。
市场区隔
公司
按类型分類的细分市场
应用领域
按地区
The global market for Cloud Robotics was estimated to be worth US$ 852 million in 2024 and is forecast to a readjusted size of US$ 1973 million by 2031 with a CAGR of 12.5% during the forecast period 2025-2031.
Cloud robotics is an emerging field of robotics rooted in cloud computing, cloud storage, and other Internet technologies centered around the benefits of converged infrastructure and shared services. It allows robots to benefit from the powerful computational, storage, and communications resources of modern data centers. In addition, it removes overheads for maintenance and updates, and reduces dependence on custom middleware.
The main market drivers include the following:
Technological innovation drives the expansion of functional boundaries
Cloud robots achieve a balance between computing power and cost through a "cloud brain + edge execution" architecture. This is driven by technological breakthroughs. On the one hand, the widespread adoption of 5G networks and the improvement of edge computing capabilities are enabling robots to collect real-time data and make low-latency decisions. For example, remote surgical robots achieve millimeter-level precision through cloud-based AI assistance. On the other hand, the integration of multimodal perception technologies (such as 3D vision and tactile sensors) with lightweight models empowers robots with enhanced environmental adaptability. For example, industrial inspection robots can autonomously identify equipment faults and generate repair plans. Furthermore, the deep integration of large AI models with robot control systems is driving the evolution from "programmed execution" to "cognitive autonomy." For example, service robots use natural language processing to understand user needs and dynamically adjust service processes.
Diversified application scenarios are driving explosive market demand
Cloud robots are expanding beyond single industrial scenarios into diverse fields, forming a large-scale application ecosystem. In industrial manufacturing, the demand for flexible production is driving the coordinated operation of robot swarms. For example, automotive welding workshops use cloud-based scheduling to enable dynamic path planning for multiple robots, improving production efficiency. In healthcare, remote surgery and rehabilitation care are becoming essential. For example, orthopedic surgical robots leverage 5G and cloud computing power to support real-time expert guidance across locations. In emergency rescue, cloud robots can replace humans in dangerous environments, such as locating survivors in earthquake debris through autonomous navigation and image recognition. Furthermore, intelligent upgrades in scenarios such as home services and logistics warehousing are further expanding the market. For example, sweeping robots can update their cleaning algorithms through the cloud to adapt to different household needs.
Policy Support and Industry Collaboration Build the Foundation for Development
Globally, strategic upgrades in intelligent manufacturing and the robotics industry are providing policy dividends for cloud robots. China's 14th Five-Year Plan explicitly lists robotics as a key development direction, accelerating the implementation of this technology through subsidies and pilot programs. Germany's Industry 4.0 initiative promotes the digitalization of manufacturing, requiring companies to deploy intelligent equipment with cloud-based collaboration capabilities. The US National Robotics Initiative focuses on key sectors such as healthcare and defense, supporting the research and development of core cloud robotics technologies. At the same time, collaborative innovation across the industry chain is lowering the barrier to entry for adoption: chip companies are launching low-power AI computing modules, communications companies are optimizing 5G private network solutions, and software companies are developing standardized cloud platforms, jointly building a closed "hardware-connectivity-algorithm" ecosystem. For example, Danghong Technology's ultra-low-latency remote control system, leveraging multimodal compression and global communication technologies, addresses signal blind spots in remote areas and promotes the widespread adoption of cloud robots in scenarios such as power inspections.
This report aims to provide a comprehensive presentation of the global market for Cloud Robotics, focusing on the total sales revenue, key companies market share and ranking, together with an analysis of Cloud Robotics by region & country, by Type, and by Application.
The Cloud Robotics market size, estimations, and forecasts are provided in terms of sales revenue ($ millions), considering 2024 as the base year, with history and forecast data for the period from 2020 to 2031. With both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyze their position in the current marketplace, and make informed business decisions regarding Cloud Robotics.
Market Segmentation
By Company
Segment by Type
Segment by Application
By Region
Chapter Outline
Chapter 1: Introduces the report scope of the report, global total market size. This chapter also provides the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by manufacturers in the industry, and the analysis of relevant policies in the industry.
Chapter 2: Detailed analysis of Cloud Robotics company competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 3: Provides the analysis of various market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 4: Provides the analysis of various market segments by Application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 5: Revenue of Cloud Robotics in regional level. It provides a quantitative analysis of the market size and development potential of each region and introduces the market development, future development prospects, market space, and market size of each country in the world.
Chapter 6: Revenue of Cloud Robotics in country level. It provides sigmate data by Type, and by Application for each country/region.
Chapter 7: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product revenue, gross margin, product introduction, recent development, etc.
Chapter 8: Analysis of industrial chain, including the upstream and downstream of the industry.
Chapter 9: Conclusion.