Mobile Robots Market, Opportunity, Growth Drivers, Industry Trend Analysis and Forecast, 2025-2034
Description
The Global Mobile Robots Market was valued at USD 11.9 billion in 2024 and is estimated to grow at a CAGR of 18.2%, to reach USD 61.1 billion by 2034.
The market growth is driven by rapid advancements in artificial intelligence, sensor technologies, and automation across various industries including logistics, defense, healthcare, and agriculture. Mobile robots, which can move autonomously within environments using advanced navigation systems, are increasingly used to enhance productivity, reduce labor costs, and improve operational safety. Their deployment has expanded significantly with the rise of Industry 4.0, smart warehouses, and contactless delivery solutions. Mobile robots play a key role in tasks such as material handling, surveillance, inventory management, and sanitation—tasks that require precision, efficiency, and the ability to operate continuously with minimal human intervention. The COVID-19 pandemic further accelerated the adoption of autonomous mobile systems, especially in healthcare and e-commerce logistics, to reduce human contact. Continuous innovation in software platforms, LiDAR sensors, edge computing, and battery technology is also propelling market growth. Governments and corporations are investing heavily in robotics R&D to meet growing demand for automation in labor-intensive environments. As integration costs decrease and performance improves, mobile robots are becoming an essential part of modern operations across sectors, setting the stage for exponential market growth over the next decade.
By product type, autonomous mobile robots (AMRs) segment generated USD 4.6 billion in 2024. AMRs have emerged as the preferred choice across multiple sectors due to their ability to navigate dynamic environments without predefined paths or human supervision. These robots rely on real-time data from onboard sensors and AI-powered mapping systems to make smart navigation decisions, enabling efficient workflow automation in manufacturing, healthcare, and warehousing. Their flexibility and adaptability allow organizations to scale operations without redesigning floor layouts or infrastructure. With rising labor shortages and growing demand for 24/7 operations, AMRs are increasingly being integrated into last-mile delivery systems, hospital services, and precision farming, among other applications.
In 2024, the manufacturing segment accounted for USD 3.2 billion, driven by the growing need for automation, operational efficiency, and workplace safety in production environments. Mobile robots are increasingly being used in manufacturing facilities to transport raw materials, components, and finished goods across factory floors, reducing reliance on manual labor and streamlining intra-logistics operations. These robots help minimize production downtime, increase throughput, and optimize space utilization—particularly in lean manufacturing setups.
Asia Pacific Mobile Robots Market generated USD 8.2 billion in 2024 driven by rapid industrialization, massive logistics networks, and government-supported automation initiatives in countries such as China, Japan, and South Korea. The region's large-scale manufacturing base, combined with rising labor costs and strong technology adoption, is accelerating demand for mobile robotic solutions in assembly lines, packaging, and material transport. China is investing heavily in robotics under its “Made in China 2025” initiative, aiming to reduce dependence on foreign automation technologies. Additionally, Japan's aging workforce and South Korea's tech leadership have made mobile robots critical in healthcare, elderly care, and smart manufacturing applications.
Key companies driving innovation and expansion in the mobile robots market include Boston Dynamics, KUKA AG, iRobot Corporation, OMRON Corporation, Locus Robotics, Clearpath Robotics, Fetch Robotics (Zebra Technologies), GreyOrange, Mobile Industrial Robots (Teradyne Inc.), and Seegrid Corporation. These players are focused on enhancing autonomy, mobility, and AI integration through strategic partnerships, acquisitions, and continuous R&D investment, ensuring their leadership in an increasingly competitive and fast-growing market.
The market growth is driven by rapid advancements in artificial intelligence, sensor technologies, and automation across various industries including logistics, defense, healthcare, and agriculture. Mobile robots, which can move autonomously within environments using advanced navigation systems, are increasingly used to enhance productivity, reduce labor costs, and improve operational safety. Their deployment has expanded significantly with the rise of Industry 4.0, smart warehouses, and contactless delivery solutions. Mobile robots play a key role in tasks such as material handling, surveillance, inventory management, and sanitation—tasks that require precision, efficiency, and the ability to operate continuously with minimal human intervention. The COVID-19 pandemic further accelerated the adoption of autonomous mobile systems, especially in healthcare and e-commerce logistics, to reduce human contact. Continuous innovation in software platforms, LiDAR sensors, edge computing, and battery technology is also propelling market growth. Governments and corporations are investing heavily in robotics R&D to meet growing demand for automation in labor-intensive environments. As integration costs decrease and performance improves, mobile robots are becoming an essential part of modern operations across sectors, setting the stage for exponential market growth over the next decade.
By product type, autonomous mobile robots (AMRs) segment generated USD 4.6 billion in 2024. AMRs have emerged as the preferred choice across multiple sectors due to their ability to navigate dynamic environments without predefined paths or human supervision. These robots rely on real-time data from onboard sensors and AI-powered mapping systems to make smart navigation decisions, enabling efficient workflow automation in manufacturing, healthcare, and warehousing. Their flexibility and adaptability allow organizations to scale operations without redesigning floor layouts or infrastructure. With rising labor shortages and growing demand for 24/7 operations, AMRs are increasingly being integrated into last-mile delivery systems, hospital services, and precision farming, among other applications.
In 2024, the manufacturing segment accounted for USD 3.2 billion, driven by the growing need for automation, operational efficiency, and workplace safety in production environments. Mobile robots are increasingly being used in manufacturing facilities to transport raw materials, components, and finished goods across factory floors, reducing reliance on manual labor and streamlining intra-logistics operations. These robots help minimize production downtime, increase throughput, and optimize space utilization—particularly in lean manufacturing setups.
Asia Pacific Mobile Robots Market generated USD 8.2 billion in 2024 driven by rapid industrialization, massive logistics networks, and government-supported automation initiatives in countries such as China, Japan, and South Korea. The region's large-scale manufacturing base, combined with rising labor costs and strong technology adoption, is accelerating demand for mobile robotic solutions in assembly lines, packaging, and material transport. China is investing heavily in robotics under its “Made in China 2025” initiative, aiming to reduce dependence on foreign automation technologies. Additionally, Japan's aging workforce and South Korea's tech leadership have made mobile robots critical in healthcare, elderly care, and smart manufacturing applications.
Key companies driving innovation and expansion in the mobile robots market include Boston Dynamics, KUKA AG, iRobot Corporation, OMRON Corporation, Locus Robotics, Clearpath Robotics, Fetch Robotics (Zebra Technologies), GreyOrange, Mobile Industrial Robots (Teradyne Inc.), and Seegrid Corporation. These players are focused on enhancing autonomy, mobility, and AI integration through strategic partnerships, acquisitions, and continuous R&D investment, ensuring their leadership in an increasingly competitive and fast-growing market.
Table of Contents
236 Pages
- Chapter 1: Methodology
- 1.1. Definitions
- 1.2. Research Design
- 1.2.1. Research approach
- 1.2.2. Data collection methods
- 1.2.3. Base estimates and calculations
- 1.2.4. Base year calculation
- 1.2.5. Key trends for market estimates
- 1.3. Forecast model
- 1.4. Primary research & validation
- 1.5. Some of the primary sources (but not limited to):
- 1.5.1. Inputs from primary interviews:
- 1.6. Data Mining Sources
- 1.6.1. Secondary Sources
- 1.6.1.1. Paid Sources
- 1.6.1.2. Public Sources
- 1.7. Sources, by region
- Chapter 2: Executive Summary
- 2.1. Industry snapshot
- 2.2. Business trends
- 2.3. Robot type trends
- 2.4. Navigation technology trends
- 2.5. Battery type trends
- 2.6. Payload capacity trends
- 2.7. Application trends
- 2.8. End-use industry trends
- 2.9. Regional trends
- Chapter 3: Industry Insights
- 3.1. Industry snapshot
- 3.1.1. Components Suppliers
- 3.1.2. Robot Manufacturers
- 3.1.3. System Integrators
- 3.1.4. Software providers
- 3.1.5. End user
- 3.1.6. Vendor matrix
- 3.1.7. Profit margin analysis
- 3.2. Trump Administration Tariffs Analysis
- 3.2.1. Trade impact
- 3.2.1.1. Trade volume disruptions
- 3.2.1.2. Country-wise response
- 3.2.2. Industry impact
- 3.2.2.1. Supply-side impact
- 3.2.2.1.1. Price volatility in key materials
- 3.2.2.1.2. Supply chain restructuring
- 3.2.2.1.3. Production cost implications
- 3.2.2.2. Demand-side impact (cost to consumers)
- 3.2.2.2.1. Price transmission to end markets
- 3.2.2.2.2. Market share dynamics
- 3.2.2.2.3. Consumer response patterns
- 3.2.3. Strategic industry responses
- 3.2.3.1. Supply chain reconfiguration
- 3.2.3.2. Pricing and product strategies
- 3.2.3.3. Policy engagement
- 3.2.4. Outlook and future considerations
- 3.3. Industry impact forces
- 3.3.1. Impact forces
- 3.3.2. Growth drivers
- 3.3.2.1. Rising Labor Costs and Workforce Shortages
- 3.3.2.2. Increasing Demand for Automation in Manufacturing and Logistics
- 3.3.2.3. Growth in E-commerce and Warehouse Automation
- 3.3.2.4. Technological Advancements in AI, ML, and Sensor Technologies
- 3.3.2.5. Need for Enhanced Operational Efficiency and Productivity
- 3.3.3. Pitfalls & challenges
- 3.3.3.1. High Initial Investment Costs
- 3.3.3.2. Technical Limitations and Integration Challenges
- 3.4. Growth Potential
- 3.5. Market Opportunities
- 3.5.1. Emerging Applications in Healthcare, Retail, and Agriculture
- 3.5.2. Integration with IoT and Industry
- 4.0 Technologies
- 3.5.3. Robotics-as-a-Service (RaaS) Business Models
- 3.5.4. Untapped Markets in Developing Economies
- 3.5.5. Customized Solutions for Specific Industry Needs
- 3.6. Market Challenges
- 3.6.1. Interoperability and Standardization Issues
- 3.6.2. Skilled Workforce Requirements
- 3.6.3. Return on Investment (ROI) Concerns
- 3.6.4. Environmental and Operational Constraints
- 3.6.5. Ethical and Social Implications of Automation
- 3.7. Porter’s Analysis
- 3.8. PESTEL Analysis
- 3.9. Evolution of Mobile Robotics Technology
- 3.10. Distinction Between AGVs and AMRs
- 3.10.1. Technical Specifications and Capabilities
- 3.10.2. Navigation Systems and Intelligence
- 3.10.3. Operational Flexibility and Adaptability
- 3.11. Regulatory landscape
- 3.11.1. International
- 3.11.1.1.ISO 8373:2021
- 3.11.1.2.ISO 10218-1/2
- 3.11.1.3.ISO/TS 15066
- 3.11.1.4.ISO 13482:2014
- 3.11.1.5.ISO 3691-4
- 3.11.1.6.IEC 61508
- 3.11.1.7.ISO 12100
- 3.11.2. North America
- 3.11.2.1.ANSI/RIA R
- 15.06-2012
- 3.11.2.2.ANSI/RIA R
- 15.08-1-2020
- 3.11.2.3.ANSI/RIA R
- 15.08-2-2023
- 3.11.2.4.ANSI/ITSDF B
- 56.5-2019
- 3.11.2.5.UL 3100
- 3.11.2.6.OSHA General Duty Clause (Section 5(a)(1))
- 3.11.2.7.OSHA 29 CFR
- 1910.147
- 3.11.2.8.OSHA 29 CFR
- 1910.212
- 3.11.3. Europe
- 3.11.3.1.Machinery Directive 2006/42/EC
- 3.11.3.2.Machinery Regulation (EU) 2023/1230
- 3.11.3.3.EU AI Act (Regulation (EU) 2024/1689)
- 3.11.3.4.EMC Directive (2014/30/EU)
- 3.11.4. Asia Pacific
- 3.11.4.1.GB/T 20867-2007
- 3.11.4.2.JIS B 8433-1/2
- 3.11.4.3.KS B ISO 10218-1/2
- 3.11.5. Middle East & Africa
- 3.11.5.1.UAE National Strategy for Artificial Intelligence 2031
- 3.11.5.2.Dubai Robotics and Automation Program
- 3.11.5.3.Saudi Generative AI Guidelines
- 3.11.6. Latin America
- 3.11.6.1.Chile's Law 20949
- 3.11.6.2.Argentina's National Artificial Intelligence Plan
- 3.11.6.3.OECD AI Principles (adopted by several Latin American countries)
- 3.12. Future market outlook
- 3.13. Investment Analysis and Market Opportunities
- 3.13.1. Investment Trends in Mobile Robotics
- 3.13.2. Emerging Business Models
- 3.13.3. Investment Opportunities
- 3.14. Technology and innovation landscape
- 3.14.1. Current Technological Trends
- 3.14.1.1.Artificial Intelligence and Machine Learning Integration
- 3.14.1.2.Advanced Sensor Technologies
- 3.14.1.3.Cloud Robotics and IoT Integration
- 3.14.1.4.5G Connectivity and Edge Computing
- 3.14.1.5.Human-Robot Collaboration Technologies
- 3.15. Patent analysis
- 3.16. Use Cases and Application Analysis
- 3.16.1. Case Study 1: Supermarket Automation
- 3.16.2. Inventory Management
- 3.16.3. Key Learnings and Best Practices
- 3.17. Other Industry Implementations
- 3.17.1. Case Study 3: Agriculture
- 3.17.2. Case Study 4: Construction
- Chapter 4: Competitive Landscape, 2024
- 4.1. Competitive Landscape
- 4.2. Company market share analysis, 2024
- 4.3. Competitive analysis of the key market players
- 4.4. Strategic Initiative
- 4.4.1. ABB Group
- 4.4.2. Zebra Technology
- 4.4.3. KUKA AG
- 4.4.4. Omron Automation
- 4.4.5. Honda Robotics
- 4.4.6. Continental Mobile Robots
- 4.4.7. iRobot
- 4.5. Competitive Positioning Matrix
- 4.6. Strategic Outlook Matrix
- Chapter 5: Mobile Robots Market, By Robot Type
- 5.1. Robot Type Key Trends
- 5.2. Automated Guided Vehicles (AGVs)
- 5.3. Autonomous Mobile Robots (AMRs)
- 5.4. Autonomous Mobile Manipulation Robots (AMMRs)
- 5.5. Hybrid Mobile Robots
- Chapter 6: Mobile Robots Market, By Navigation Technology
- 6.1. Navigation Technology Key Trends
- 6.2. Laser Guidance
- 6.3. Vision Guidance
- 6.4. Magnetic Guidance
- 6.5. Inertial Guidance
- 6.6. Natural Navigation (SLAM)
- 6.7. Others
- Chapter 7: Mobile Robots Market, By Battery Type
- 7.1. Battery Type Key Trends
- 7.2. Lead Acid Batteries
- 7.3. Lithium-Ion Batteries
- 7.4. Nickel-Based Batteries
- 7.5. Others
- Chapter 8: Mobile Robots Market, By Payload Capacity
- 8.1. Payload Capacity Key Trends
- 8.2. Low Payload (<100 kg)
- 8.3. Medium Payload (100-500 kg)
- 8.4. High Payload (>500 kg)
- Chapter 9: Mobile Robots Market, By Application
- 9.1. Application Key Trends
- 9.2. Material Handling and Transportation
- 9.3. Picking, Packing, and Sorting
- 9.4. Warehouse and Inventory Management
- 9.5. Assembly and Disassembly
- 9.6. Cleaning and Disinfection
- 9.7. Security and Surveillance
- 9.8. Last-Mile Delivery
- 9.9. Others
- Chapter 10: Mobile Robots Market, By End-use Industry
- 10.1. End-use Industry Key Trends
- 10.2. Manufacturing
- 10.3. Logistics and Warehousing
- 10.4. Healthcare and Pharmaceuticals
- 10.5. Retail and Consumer Goods
- 10.6. Agriculture and Farming
- 10.7. Construction and Mining
- 10.8. Military and Defense
- 10.9. Hospitality and Entertainment
- 10.10. Others
- Chapter 11: Mobile Robots Market, By Region
- 11.1. Region Key Trends
- 11.2. North America
- 11.3. Europe
- 11.4. Asia Pacific
- 11.5. Latin America
- 11.6. Middle East & Africa (MEA)
- Chapter 12: Company Profile
- 12.1. ABB Ltd.
- 12.1.1. Financial Data
- 12.1.2. Product Landscape
- 12.1.3. Strategic Outlook
- 12.1.4. SWOT Analysis
- 12.2. Aethon
- 12.2.1. Financial Data
- 12.2.2. Product Landscape
- 12.2.3. SWOT Analysis
- 12.3. AGILOX
- 12.3.1. Financial Data
- 12.3.2. Product Landscape
- 12.3.3. Strategic Outlook
- 12.3.4. SWOT Analysis
- 12.4. Continental Mobile Robots
- 12.4.1. Financial Data
- 12.4.2. Product Landscape
- 12.4.3. Strategic Outlook
- 12.4.4. SWOT Analysis
- 12.5. Honda Robotics
- 12.5.1. Financial Data
- 12.5.2. Product Landscape
- 12.5.3. Strategic Outlook
- 12.5.4. SWOT Analysis
- 12.6. iRobot Corporation
- 12.6.1. Financial Data
- 12.6.2. Product Landscape
- 12.6.3. Strategic Outlook
- 12.6.4. SWOT Analysis
- 12.7. KUKA AG
- 12.7.1. Financial Data
- 12.7.2. Product Landscape
- 12.7.3. SWOT Analysis
- 12.8. Locus Robotics
- 12.8.1. Financial Data
- 12.8.2. Product Landscape
- 12.8.3. SWOT Analysis
- 12.9. Mobile Industrial Robots
- 12.9.1. Financial Data
- 12.9.2. Product Landscape
- 12.9.3. SWOT Analysis
- 12.10. Omron Corporation
- 12.10.1. Financial Data
- 12.10.2. Product Landscape
- 12.10.3. Strategic Outlook
- 12.10.4. SWOT Analysis
- 12.11. Robotize
- 12.11.1. Financial Data
- 12.11.2. Product Landscape
- 12.11.3. Strategic Outlook
- 12.11.4. SWOT Analysis
- 12.12. Zebra Technologies
- 12.12.1. Financial Data
- 12.12.2. Product Landscape
- 12.12.3. SWOT Analysis
- Chapter 13: Appendix
- 13.1. Market Definitions
- 13.2. Related Studies
- 13.3. Research practices
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