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全球仓储人工智慧机器人市场：按功能/应用、机器人类型、人工智慧能力、部署模式、最终用户/产业、自主层级和地区划分－市场规模、产业动态、机会分析和预测（2026-2035 年）

Global AI Robotics in Warehousing Market: By Function / Application, Robot Type, AI Capability, Deployment Mode, End User / Industry, Autonomy Level, Region - Market Size, Industry Dynamics, Opportunity Analysis and Forecast for 2026-2035

出版日期: 2026年03月19日 | 出版商:

Astute Analytica | 英文 310 Pages | 商品交期: 最快1-2个工作天内

价格

简介目录

全球仓库人工智慧机器人市场正经历快速且变革性的扩张，反映出自动化在现代价值链中日益增长的重要性。该市场在2025年的价值为125.7亿美元，预计到2035年将达到1026.7亿美元。这一显着成长意味着在2026年至2035年的预测期内，复合年增长率将达到23.37%。如此快速的成长凸显了人工智慧驱动机器人的加速普及，因为全球仓库都在努力满足日益增长的效率、速度和准确性需求。

推动该市场快速成长的因素有很多。电子商务的扩张是主要驱动力之一，因为线上零售不断改变消费者的行为，强调快速配送和丰富的产品种类。为了满足这些需求，仓库需要更快、更精准地运作，这使得能够自动化拣货、包装、分类和库存管理等复杂任务的先进机器人系统变得至关重要。此外，仓储业普遍存在的人手不足也加速了自动化进程。

显着的市场趋势

截至2026年初，仓储人工智慧机器人市场的供应商格局正在经历一场剧烈的变革，从Start-Ups的新创企业生态系统演变为由产业巨头和高度专业化的人工智慧颠覆者主导的激烈竞争格局。这种转变反映了市场的成熟，规模、技术水平和战略伙伴关係如今已成为成功的关键因素。在主要企业中，Geek+ 已成为全球自主移动机器人 (AMR) 部署量最大的企业，并在货到人 (G2P) 解决方案领域占据了约50%的全球市场份额。

在高密度立方体储存和食品杂货自动化领域，AutoStore 和 Symbotic 已成为主要企业。 AutoStore 的模组化、节省空间的储存系统革新了仓库设计，使企业能够在有限的空间内最大限度地提高储存容量。同时，Symbotic 透过与美国主要零售商建立深度合作关係，确立了行业领先地位，并为全面的端到端自动化解决方案树立了行业标准。

Locus Robotics 已成为协作式自主移动机器人（简称协作机器人）领域的领导企业，其产品专为履约营运而设计。 Locus Robotics 以其高效的机器人即服务 (RaaS) 模式和直觉的多机器人编配软体而备受讚誉，提供扩充性且易于使用的解决方案。他们的协作机器人可与人类操作员协同工作，在无需大规模基础设施改造的情况下提高生产效率。

主要成长驱动因素

仓库人事费用不断上涨，加上技术纯熟劳工短缺，正在加速向机器人解决方案的转型，并成为仓储行业市场成长的主要驱动力。随着薪资上涨和对熟练人员的竞争持续推高人事费用，企业面临着在保持高生产力的同时降低营运成本的压力。这些财务负担迫使仓库业者探索采用自动化技术，以实现稳定的绩效，同时避免人工操作带来的许多挑战，例如离职率、需要培训以及员工缺勤等问题。

新机会的趋势

全球零售和物流公司的巨额投资正在为机器人仓储市场创造机会，预计将推动该市场快速扩张和创新。这些行业面临着提高效率、降低人事费用以及满足消费者日益增长的快速配送需求的压力，因此正将机器人技术视为关键解决方案。来自全球主要企业的资金涌入正在推动先进机器人系统的研发和应用，使仓库能够自动化执行更复杂的任务，并更有效地扩展营运规模。

优化障碍

电池劣化和充电瓶颈是阻碍人工智慧机器人市场成长的重大挑战，尤其是在高度依赖自主移动机器人（AMR）的仓库环境中。随着机器人数量的增加，充电基础设施的压力日益凸显。例如，运行200台AMR需要大规模、设计完善的充电设施，以支援其持续运作。如果没有充足的基础设施和智慧管理，充电很快就会成为主要的营运瓶颈。

产业价值链分析
- 元件供应商
- 机器人製造商
- 软体和人工智慧解决方案供应商
- 系统整合商
- 最终用户
产业展望
- 仓库自动化的发展
- 物流业人工智慧应用趋势
PESTLE分析
波特五力分析
- 供应商的议价能力
- 买方的议价能力
- 替代品的威胁
- 新进入者的威胁
- 竞争强度
市场成长及前景
- 市场收入估算与预测（2020-2035 年）
- 价格趋势分析

第四章：全球仓储人工智慧机器人市场分析

竞争格局仪錶板
- 市场集中度
- 企业市场占有率分析（以金额为准，%），2025 年
- 竞争对手分析与基准测试

第五章：全球仓储人工智慧机器人市场分析

市场动态和趋势
- 成长驱动因素
- 抑制因子
- 机会
- 主要趋势
市场规模及预测（2020-2035）
- 透过人工智慧功能
- 按机器人类型
- 自主等级
- 依部署类型
- 按功能/用途
- 最终用户/行业特定
- 按地区

第六章：北美市场分析

第七章：欧洲市场分析

第八章：亚太市场分析

第九章：中东和非洲市场分析

第十章：南美市场分析

第十一章：公司简介

Yaskawa Electric Corporation
Amazon Robotics
Boston Dynamics
Cognex Corporation
Dematic（KION Group）
Elettric 80 SpA
ABB Ltd.
FANUC Corporation
Fetch Robotics
Geek+
GreyOrange
KUKA AG
Locus Robotics
Magazino GmbH
Mobile Industrial Robots（MiR）
Honeywell Intelligrated
Omron Corporation
Swisslog（KUKA Group）
Teradyne Inc.（Adept Technology）
其他主要企业

第十二章附录

简介目录

Product Code: AA03261735

The global AI robotics in warehousing market is undergoing rapid and transformative expansion, reflecting the growing importance of automation in modern supply chains. In 2025, the market was valued at USD 12.57 billion, and it is projected to reach an impressive USD 102.67 billion by 2035. This remarkable growth corresponds to a compound annual growth rate (CAGR) of 23.37% during the forecast period from 2026 to 2035. Such a steep rise highlights the accelerating adoption of AI-driven robotics as warehouses worldwide strive to meet the increasing demands of efficiency, speed, and accuracy.

Several key factors are driving this market surge. The expansion of e-commerce is a primary catalyst, as online retail continues to reshape consumer behavior by emphasizing fast delivery and vast product assortments. To keep pace with these expectations, warehouses must operate at higher speeds and with greater precision, necessitating advanced robotic systems that can automate complex tasks such as picking, packing, sorting, and inventory management. Additionally, widespread labor shortages in the warehousing sector are intensifying the push towards automation.

Noteworthy Market Developments

As of early 2026, the vendor landscape in the AI robotics in warehousing market has undergone a dramatic transformation, evolving from a fragmented startup ecosystem into a fiercely competitive arena dominated by both consolidated industry giants and hyper-specialized AI disruptors. This shift reflects the maturation of the market, where scale, technological sophistication, and strategic partnerships now define success. Among the leaders, Geek+ stands out as the global volume champion in Autonomous Mobile Robot (AMR) deployment, commanding nearly 50% of the global market share in goods-to-person (G2P) solutions.

In the realm of high-density cubic storage and grocery automation, AutoStore and Symbotic have established themselves as the key players. AutoStore's modular and space-efficient storage system has revolutionized warehouse design, allowing companies to maximize storage capacity in limited spaces. Symbotic, meanwhile, has carved out a leadership position through its deep integration with major U.S. retailers, setting the industry standard for comprehensive end-to-end automation solutions.

Locus Robotics has emerged as the undeniable leader in collaborative AMRs, commonly known as cobots, designed specifically for fulfillment operations. Celebrated for its highly effective Robotics-as-a-Service (RaaS) model and intuitive multi-robot orchestration software, Locus offers a solution that is both scalable and user-friendly. Their cobots work alongside human operators, enhancing productivity without requiring extensive infrastructure changes.

Core Growth Drivers

Increasing warehouse labor costs, coupled with a scarcity of skilled workers, are major factors accelerating the shift toward robotic solutions and driving market growth in the warehousing sector. As labor expenses continue to rise, fueled by wage inflation and heightened competition for qualified personnel, companies face mounting pressure to control operational costs while maintaining high levels of productivity. This financial strain compels warehouse operators to explore automation technologies that can deliver consistent performance without the challenges associated with human labor, such as turnover, training needs, and absenteeism.

Emerging Opportunity Trends

High investment from global retail and logistics companies is expected to create favorable opportunities for the robotics warehousing market, driving rapid expansion and innovation. As these industries face increasing pressure to enhance efficiency, reduce labor costs, and meet growing consumer demand for faster delivery times, they are turning to robotics as a critical solution. The influx of capital from major players worldwide is fueling research, development, and deployment of advanced robotic systems, enabling warehouses to automate more complex tasks and scale operations more effectively.

Barriers to Optimization

Battery degradation and charging bottlenecks present significant challenges that could hamper growth in the AI robotics market, particularly in warehouse environments relying heavily on Autonomous Mobile Robots (AMRs). As fleets expand, the strain on charging infrastructure becomes increasingly apparent. For example, managing a fleet of 200 AMRs requires a well-designed and extensive charging setup capable of supporting continuous operations. Without adequate infrastructure and intelligent management, charging can quickly become a major operational bottleneck.

Detailed Market Segmentation

By robot type, the Automated Guided Vehicles (AGVs) segment commanded a substantial 41% market share in 2024, highlighting their pivotal role in industrial automation and logistics. AGVs have earned a reputation as one of the most dependable and mature robotic technologies available, making them a preferred choice for companies seeking to modernize their operations while minimizing risks. Their proven track record in heavy industry and legacy logistics environments underscores their reliability and effectiveness in handling repetitive material transport tasks in complex and often harsh conditions.

By function and application, the picking and packing segment emerged as the leader in the AI robotics in warehousing market, holding an estimated 39% market share in 2025. This dominance highlights the critical importance of these processes within warehouse operations, where efficiency and accuracy directly impact overall productivity and customer satisfaction. Order picking, in particular, has long been recognized as one of the most labor-intensive and costly activities in traditional logistics, historically accounting for 50% to 55% of total warehouse operating expenses. This significant cost burden has driven companies to seek automation solutions that can streamline picking and packing tasks, reduce errors, and lower labor costs.

By AI capability, the machine learning (ML) and predictive analytics segment established its dominance over the market in 2024, capturing a commanding 42.22% share. This strong foothold underscores the critical role that ML and predictive analytics play in elevating robotic systems from basic automated devices to intelligent, adaptive machines capable of complex decision-making. Without these AI capabilities, a robot's functionality is severely limited, akin to an expensive remote-controlled car that can only follow pre-programmed commands without learning or adapting to its environment.

By end users, the e-commerce and omni-channel retail sector dominates the market with a commanding 44% share, reflecting its critical role in shaping logistics and fulfillment strategies. This prominence is largely driven by the increasing demand for micro-fulfillment centers and the pressure to meet stringent same-day delivery service level agreements (SLAs). As consumer expectations for rapid and reliable delivery continue to rise, retailers are compelled to adopt advanced automation solutions that can handle the complexity and scale of modern order fulfillment.

Segment Breakdown

By AI Capability

Machine Learning & Predictive Analytics
Computer Vision & Imaging
Sensor Fusion & IoT Integration
Natural Language Processing (NLP)
Autonomous Navigation & Path Planning
Others

By Robot Type

Automated Guided Vehicles (AGVs)
Towing AGVs
Unit Load AGVs
Autonomous Mobile Robots (AMRs)
Picking AMRs
Pallet Handling AMRs
Robotic Arms & Pick-and-Place Robots
Collaborative Robots (Cobots)
Sorting & Packaging Robots
Others

By Function / Application

Picking & Packing
Sorting & Distribution
Inventory Management & Tracking
Material Transport & Handling
Loading & Unloading
Quality Inspection
Others

By End User / Industry

E-Commerce & Retail
Third-Party Logistics Providers (3PLs)
Food & Beverage
Pharmaceuticals & Healthcare
Consumer Goods
Industrial & Manufacturing
Others

By Deployment Mode

On-Premises
Cloud-Integrated Edge Systems

By Autonomy Level

Semi-Autonomous Robots
Fully Autonomous Robots

By Region

North America
The U.S.
Canada
Mexico
Europe
Western Europe
The UK
Germany
France
Italy
Spain
Rest of Western Europe
Eastern Europe
Poland
Russia
Rest of Eastern Europe
Asia Pacific
China
India
Japan
Australia & New Zealand
South Korea
ASEAN
Rest of Asia Pacific
Middle East & Africa (MEA)
Saudi Arabia
South Africa
UAE
Rest of MEA
South America
Argentina
Brazil
Rest of South America

Geography Breakdown

North America commands a significant 41% share of the global market for AI robotics in warehousing, reflecting the region's proactive approach to addressing critical labor and operational challenges. In both the United States and Canada, the adoption of warehouse robotics is seen as a strategic offensive measure aimed at countering the effects of severe wage inflation and rising labor costs. Warehouse wages in the region have surged beyond $22 per hour, creating substantial pressure on companies to find cost-effective solutions that maintain productivity without escalating expenses. At the same time, warehouses face brutal labor turnover rates exceeding 40%, which disrupts operations and increases recruitment and training costs.
Within this context, North American supply chain executives are prioritizing solutions that offer more than just inexpensive hardware. Their focus has shifted toward Robotics-as-a-Service (RaaS) models and the seamless integration of advanced software systems. Unlike traditional capital expenditure-heavy investments in robotics equipment, RaaS allows companies to treat automation as an operational expense (OpEx), bypassing the often lengthy and challenging capital expenditure (CapEx) approval processes. This flexibility enables warehouses to rapidly deploy robotic systems and scale operations according to demand without the upfront financial burden.
As a result, the North American market for AI robotics in warehousing is characterized by sophisticated, flexible approaches that emphasize operational agility and cost management. The region's supply chain leaders are leveraging RaaS and advanced software capabilities to mitigate labor challenges and to enhance overall warehouse efficiency and competitiveness.

Leading Market Participants

Yaskawa Electric Corporation
Amazon Robotics
Boston Dynamics
Cognex Corporation
Dematic (KION Group)
Elettric 80 S.p.A.
ABB Ltd.
FANUC Corporation
Fetch Robotics
Geek+
GreyOrange
KUKA AG
Locus Robotics
Magazino GmbH
Mobile Industrial Robots (MiR)
Honeywell Intelligrated
Omron Corporation
Swisslog (KUKA Group)
Teradyne Inc. (Adept Technology)

Table of Content

Chapter 1. Executive Summary: Global AI Robotics In Warehousing Market

Chapter 2. Research Methodology & Research Framework

2.1. Research Objective
2.2. Product Overview
2.3. Market Segmentation
2.4. Qualitative Research
- 2.4.1. Primary & Secondary Sources
2.5. Quantitative Research
- 2.5.1. Primary & Secondary Sources
2.6. Breakdown of Primary Research Respondents, By Region
2.7. Assumption for Study
2.8. Market Size Estimation
2.9. Data Triangulation

Chapter 3. Global AI Robotics In Warehousing Market Overview

3.1. Industry Value Chain Analysis
- 3.1.1. Component Suppliers
- 3.1.2. Robotics Manufacturers
- 3.1.3. Software & AI Solution Providers
- 3.1.4. System Integrators
- 3.1.5. End Users
3.2. Industry Outlook
- 3.2.1. Evolution of Warehouse Automation
- 3.2.2. Adoption Trends of AI in Logistics
3.3. PESTLE Analysis
3.4. Porter's Five Forces Analysis
- 3.4.1. Bargaining Power of Suppliers
- 3.4.2. Bargaining Power of Buyers
- 3.4.3. Threat of Substitutes
- 3.4.4. Threat of New Entrants
- 3.4.5. Degree of Competition
3.5. Market Growth and Outlook
- 3.5.1. Market Revenue Estimates and Forecast (US$ Mn), 2020-2035
- 3.5.2. Price Trend Analysis

Chapter 4. Global AI Robotics In Warehousing Market Analysis

4.1. Competition Dashboard
- 4.1.1. Market Concentration Rate
- 4.1.2. Company Market Share Analysis (Value %), 2025
- 4.1.3. Competitor Mapping & Benchmarking

Chapter 5. Global AI Robotics In Warehousing Market Analysis

5.1. Market Dynamics and Trends
- 5.1.1. Growth Drivers
- 5.1.2. Restraints
- 5.1.3. Opportunity
- 5.1.4. Key Trends
5.2. Market Size and Forecast, 2020-2035 (US$ Mn)
- 5.2.1. By AI Capability
  - 5.2.1.1. Key Insights
    - 5.2.1.1.1. Machine Learning & Predictive Analytics
    - 5.2.1.1.2. Computer Vision & Imaging
    - 5.2.1.1.3. Sensor Fusion & IoT Integration
    - 5.2.1.1.4. Natural Language Processing (NLP)
    - 5.2.1.1.5. Autonomous Navigation & Path Planning
    - 5.2.1.1.6. Others
- 5.2.2. By Robot Type
  - 5.2.2.1. Key Insights
    - 5.2.2.1.1. Automated Guided Vehicles (AGVs)
      - 5.2.2.1.1.1. Towing AGVs
      - 5.2.2.1.1.2. Unit Load AGVs
    - 5.2.2.1.2. Autonomous Mobile Robots (AMRs)
      - 5.2.2.1.2.1. Picking AMRs
      - 5.2.2.1.2.2. Pallet Handling AMRs
    - 5.2.2.1.3. Robotic Arms & Pick-and-Place Robots
    - 5.2.2.1.4. Collaborative Robots (Cobots)
    - 5.2.2.1.5. Sorting & Packaging Robots
    - 5.2.2.1.6. Others
- 5.2.3. By Autonomy Level
  - 5.2.3.1. Key Insights
    - 5.2.3.1.1. Semi-Autonomous Robots
    - 5.2.3.1.2. Fully Autonomous Robots
- 5.2.4. By Deployment Mode
  - 5.2.4.1. Key Insights
    - 5.2.4.1.1. On-Premises
    - 5.2.4.1.2. Cloud-Integrated Edge Systems
- 5.2.5. By Function / Application
  - 5.2.5.1. Key Insights
    - 5.2.5.1.1. Picking & Packing
    - 5.2.5.1.2. Sorting & Distribution
    - 5.2.5.1.3. Inventory Management & Tracking
    - 5.2.5.1.4. Material Transport & Handling
    - 5.2.5.1.5. Loading & Unloading
    - 5.2.5.1.6. Quality Inspection
    - 5.2.5.1.7. Others
- 5.2.6. By End User / Industry
  - 5.2.6.1. Key Insights
    - 5.2.6.1.1. E-Commerce & Retail
    - 5.2.6.1.2. Third-Party Logistics Providers (3PLs)
    - 5.2.6.1.3. Food & Beverage
    - 5.2.6.1.4. Pharmaceuticals & Healthcare
    - 5.2.6.1.5. Consumer Goods
    - 5.2.6.1.6. Industrial & Manufacturing
    - 5.2.6.1.7. Others
- 5.2.7. By Region
  - 5.2.7.1. Key Insights
    - 5.2.7.1.1. North America
      - 5.2.7.1.1.1. The U.S.
      - 5.2.7.1.1.2. Canada
      - 5.2.7.1.1.3. Mexico
    - 5.2.7.1.2. Europe
      - 5.2.7.1.2.1. Western Europe
        
        5.2.7.1.2.1.1. The UK
        5.2.7.1.2.1.2. Germany
        5.2.7.1.2.1.3. France
        5.2.7.1.2.1.4. Italy
        5.2.7.1.2.1.5. Spain
        5.2.7.1.2.1.6. Rest of Western Europe
      - 5.2.7.1.2.2. Eastern Europe
        
        5.2.7.1.2.2.1. Poland
        5.2.7.1.2.2.2. Russia
        5.2.7.1.2.2.3. Rest of Eastern Europe
    - 5.2.7.1.3. Asia Pacific
      - 5.2.7.1.3.1. China
      - 5.2.7.1.3.2. India
      - 5.2.7.1.3.3. Japan
      - 5.2.7.1.3.4. South Korea
      - 5.2.7.1.3.5. Australia & New Zealand
      - 5.2.7.1.3.6. ASEAN
        
        5.2.7.1.3.6.1. Indonesia
        5.2.7.1.3.6.2. Malaysia
        5.2.7.1.3.6.3. Thailand
        5.2.7.1.3.6.4. Singapore
        5.2.7.1.3.6.5. Rest of ASEAN
      - 5.2.7.1.3.7. Rest of Asia Pacific
    - 5.2.7.1.4. Middle East & Africa
      - 5.2.7.1.4.1. UAE
      - 5.2.7.1.4.2. Saudi Arabia
      - 5.2.7.1.4.3. South Africa
      - 5.2.7.1.4.4. Rest of MEA
    - 5.2.7.1.5. South America
      - 5.2.7.1.5.1. Argentina
      - 5.2.7.1.5.2. Brazil
      - 5.2.7.1.5.3. Rest of South America

Chapter 6. North America Market Analysis

6.1. Market Dynamics and Trends
- 6.1.1. Growth Drivers
- 6.1.2. Restraints
- 6.1.3. Opportunity
- 6.1.4. Key Trends
6.2. Market Size and Forecast, 2020-2035 (US$ Mn)
- 6.2.1. Key Insights
  - 6.2.1.1. By AI Capability
  - 6.2.1.2. By Robot Type
  - 6.2.1.3. By Autonomy Level
  - 6.2.1.4. By Deployment Mode
  - 6.2.1.5. By Function / Application
  - 6.2.1.6. By End User / Industry
  - 6.2.1.7. By Country

Chapter 7. Europe Market Analysis

7.1. Market Dynamics and Trends
- 7.1.1. Growth Drivers
- 7.1.2. Restraints
- 7.1.3. Opportunity
- 7.1.4. Key Trends
7.2. Market Size and Forecast, 2020-2035 (US$ Mn)
- 7.2.1. Key Insights
  - 7.2.1.1. By AI Capability
  - 7.2.1.2. By Robot Type
  - 7.2.1.3. By Autonomy Level
  - 7.2.1.4. By Deployment Mode
  - 7.2.1.5. By Function / Application
  - 7.2.1.6. By End User / Industry
  - 7.2.1.7. By Country

Chapter 8. Asia Pacific Market Analysis

8.1. Market Dynamics and Trends
- 8.1.1. Growth Drivers
- 8.1.2. Restraints
- 8.1.3. Opportunity
- 8.1.4. Key Trends
8.2. Market Size and Forecast, 2020-2035 (US$ Mn)
- 8.2.1. Key Insights
  - 8.2.1.1. By AI Capability
  - 8.2.1.2. By Robot Type
  - 8.2.1.3. By Autonomy Level
  - 8.2.1.4. By Deployment Mode
  - 8.2.1.5. By Function / Application
  - 8.2.1.6. By End User / Industry
  - 8.2.1.7. By Country

Chapter 9. Middle East & Africa Market Analysis

9.1. Market Dynamics and Trends
- 9.1.1. Growth Drivers
- 9.1.2. Restraints
- 9.1.3. Opportunity
- 9.1.4. Key Trends
9.2. Market Size and Forecast, 2020-2035 (US$ Mn)
- 9.2.1. Key Insights
  - 9.2.1.1. By AI Capability
  - 9.2.1.2. By Robot Type
  - 9.2.1.3. By Autonomy Level
  - 9.2.1.4. By Deployment Mode
  - 9.2.1.5. By Function / Application
  - 9.2.1.6. By End User / Industry
  - 9.2.1.7. By Country

Chapter 10. South America Market Analysis

10.1. Market Dynamics and Trends
- 10.1.1. Growth Drivers
- 10.1.2. Restraints
- 10.1.3. Opportunity
- 10.1.4. Key Trends
10.2. Market Size and Forecast, 2020-2035 (US$ Mn)
- 10.2.1. Key Insights
  - 10.2.1.1. By AI Capability
  - 10.2.1.2. By Robot Type
  - 10.2.1.3. By Autonomy Level
  - 10.2.1.4. By Deployment Mode
  - 10.2.1.5. By Function / Application
  - 10.2.1.6. By End User / Industry
  - 10.2.1.7. By Country

Chapter 11. Company Profile (Company Overview, Financial Matrix, Key Product landscape, Key Personnel, Key Competitors, Contact Address, and Business Strategy Outlook)

11.1. Yaskawa Electric Corporation
11.2. Amazon Robotics
11.3. Boston Dynamics
11.4. Cognex Corporation
11.5. Dematic (KION Group)
11.6. Elettric 80 S.p.A.
11.7. ABB Ltd.
11.8. FANUC Corporation
11.9. Fetch Robotics
11.10. Geek+
11.11. GreyOrange
11.12. KUKA AG
11.13. Locus Robotics
11.14. Magazino GmbH
11.15. Mobile Industrial Robots (MiR)
11.16. Honeywell Intelligrated
11.17. Omron Corporation
11.18. Swisslog (KUKA Group)
11.19. Teradyne Inc. (Adept Technology)
11.20. Other Prominent Players

Chapter 12. Annexure

12.1. List of Secondary Sources
12.2. Key Country Markets- Macro Economic Outlook/Indicators

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