물류 로봇 시장 : 시장 기회, 성장요인, 업계 동향 분석 및 예측(2026-2035년)

The Global Logistics Robots Market was valued at USD 17.8 billion in 2025 and is estimated to grow at a CAGR of 17.9% to reach USD 91.4 billion by 2035.

This sector is evolving rapidly, shaped by growing demand for automation, tighter delivery timelines, and advanced supply chain digitization. The industry is defined by its intricate ecosystem, which is marked by geographic clustering, strategic supplier relationships, and strong vertical integration. As robotics technologies mature, logistics firms are increasingly transitioning toward autonomous systems to meet rising consumer expectations and reduce operational inefficiencies. Accelerated ROI and shrinking payback windows are prompting broader deployment of intelligent robotics systems across warehouse and distribution centers. This wave of automation is reshaping logistics infrastructure by enabling higher throughput, improved accuracy, and leaner workforce dependencies, ultimately fueling growth across developed and emerging markets.

The hardware segment held a 75% share in 2025. Robotic platforms, mechanical components, and mobility systems form the foundational layer of logistics robotics solutions, enabling seamless operation in warehouse and last-mile environments. Technological advancements and research initiatives into robotics power systems are reshaping the hardware cost structures, although human involvement in logistics operations still accounts for a large portion of total expenses.

The autonomous mobile robots (AMRs) segment held a 34% share in 2025. AMRs offer significant efficiency gains over traditional automated guided vehicles due to advanced navigation systems powered by artificial intelligence, visual SLAM, and adaptive sensor technology. These capabilities allow for real-time decision-making in complex, dynamic environments, moving the segment from pilot phases into large-scale commercial deployments.

China Logistics Robots Market is expected to register a CAGR of 18.6% between 2026 and 2035, highlighting its strong growth outlook. Backed by an extensive manufacturing base and proactive government initiatives promoting automation, the country maintains a dominant position in the regional landscape. This leadership is reinforced by widespread adoption of robotic systems across warehousing, fulfillment operations, and logistics processes, enabling higher efficiency and reduced reliance on manual labor. China's market strength reflects its role as a major global hub for production and consumption, supported by a well-developed network of automated storage facilities, intelligent distribution centers, and advanced delivery frameworks that incorporate robotics and artificial intelligence.

Key industry players shaping the competitive landscape of the Global Logistics Robots Market include ABB, Yaskawa Electric, Toyota/Bastian, Omron, Daifuku, Amazon Robotics, KUKA/Swisslog, KION/Dematic, Honeywell, and AutoStore. To reinforce their position, logistics robotics companies are prioritizing AI-powered automation, real-time data analytics, and modular system designs tailored to various logistics use cases. Strategic mergers and partnerships enable technology sharing and geographic expansion, while R&D investments are yielding scalable platforms for multi-application functionality. Leading firms are also customizing robotic fleets to suit e-commerce, third-party logistics, and retail warehouse environments, ensuring long-term client retention and improved operational ROI. Global players are further strengthening their presence through localized production, expanded service networks, and integrated digital platforms that enable seamless logistics orchestration and predictive maintenance.

Table of Contents

Chapter 1 Methodology

• 1.1 Research approach
• 1.2 Quality commitments
• 1.3 Research trail and confidence scoring
  • 1.3.1 Research trail components
  • 1.3.2 Scoring components
• 1.4 Data collection
  • 1.4.1 Partial list of primary sources
• 1.5 Data mining sources
  • 1.5.1 Paid sources
• 1.6 Best estimates and calculations
  • 1.6.1 Base year calculation
• 1.7 Forecast model
• 1.8 Research transparency addendum

Chapter 2 Executive Summary

• 2.1 Industry 360° synopsis, 2022 - 2035
• 2.2 Key market trends
  • 2.2.1 Regional
  • 2.2.2 Component
  • 2.2.3 Type
  • 2.2.4 Application
  • 2.2.5 Payload Capacity
  • 2.2.6 End use
• 2.3 TAM Analysis, 2026-2035
• 2.4 CXO perspectives: Strategic imperatives

Chapter 3 Industry Insights

• 3.1 Industry ecosystem analysis
  • 3.1.1 Supplier landscape
  • 3.1.2 Profit margin analysis
  • 3.1.3 Cost structure
  • 3.1.4 Value addition at each stage
  • 3.1.5 Factor affecting the value chain
  • 3.1.6 Disruptions
• 3.2 Industry impact forces
  • 3.2.1 Growth drivers
    • 3.2.1.1 Exponential growth in e-commerce & omnichannel fulfillment demands
    • 3.2.1.2 Severe labor shortages & rising warehousing labor costs
    • 3.2.1.3 Advancements in AI, computer vision & autonomous navigation technologies
    • 3.2.1.4 Adoption of robotics-as-a-service (RaaS) business models
    • 3.2.1.5 Push for operational efficiency & supply chain resilience
  • 3.2.2 Industry pitfalls and challenges
    • 3.2.2.1 High initial capital expenditure & ROI uncertainties
    • 3.2.2.2 Integration complexity with legacy warehouse management systems
    • 3.2.2.3 Lack of interoperability between different robotic vendor systems
    • 3.2.2.4 Facility infrastructure constraints (floor quality, wireless connectivity, power)
  • 3.2.3 Market opportunities
    • 3.2.3.1 Untapped SME warehouse automation market
    • 3.2.3.2 Expansion into cold chain & temperature-controlled logistics
    • 3.2.3.3 Last-mile delivery automation using drones & autonomous vehicles
    • 3.2.3.4 Retrofitting brownfield warehouses with modular robotic solutions
    • 3.2.3.5 AI-driven predictive maintenance & fleet optimization services
• 3.3 Growth potential analysis
• 3.4 Pricing Analysis (Driven by Primary Research)
  • 3.4.1 Historical Price Trend Analysis
  • 3.4.2 Pricing Strategy by Player Type (Premium / Value / Cost-plus)
• 3.5 Regulatory landscape
  • 3.5.1 North America
    • 3.5.1.1 US- Robotics safety, automation & workplace regulations
    • 3.5.1.2 Canada - Automation safety & AI governance framework
  • 3.5.2 Europe
    • 3.5.2.1 Germany- EU Machinery Regulation & Industry 4.0 compliance
    • 3.5.2.2 UK- Post-Brexit automation & AI regulations
    • 3.5.2.3 France- AI regulation & sustainability mandates
    • 3.5.2.4 Italy- Industrial automation & workplace safety compliance
  • 3.5.3 Asia Pacific
    • 3.5.3.1 China- Robotics standards & smart logistics policies
    • 3.5.3.2 India- Industrial automation & digital logistics policies
    • 3.5.3.3 Japan- Robotics leadership & safety regulations
    • 3.5.3.4 Australia- Workplace safety & automation governance
  • 3.5.4 LATAM
    • 3.5.4.1 Mexico- Industrial automation standards & compliance
    • 3.5.4.2 Argentina- National industrial safety & automation policies
  • 3.5.5 MEA
    • 3.5.5.1 South Africa- Industrial safety & automation regulations
  • 3.5.6 Saudi Arabia- Vision 2030 & smart logistics regulations
• 3.6 Porter's analysis
• 3.7 PESTEL analysis
• 3.8 Patent Landscape (Driven by Primary Research)
• 3.9 Trade Data Analysis (Based on Paid Database)
  • 3.9.1 Import/Export Volume & Value Trends
  • 3.9.2 Key Trade Corridors & Tariff Impact
• 3.10 Impact of AI & Generative AI on the Market (Driven by Primary Research)
  • 3.10.1 AI-Driven Disruption of Existing Business Models
  • 3.10.2 GenAI Use Cases & Adoption Roadmap by Segment
  • 3.10.3 Risks, Limitations & Regulatory Considerations
• 3.11 Capacity & Production Landscape (Driven by Primary Research)
  • 3.11.1 Production Capacity by Region & Key Producer
  • 3.11.2 Capacity Utilization Rates & Expansion Pipelines
• 3.12 Technology and innovation landscape
  • 3.12.1 Current technological trends
  • 3.12.2 Emerging technologies
• 3.13 Use cases & success stories
• 3.14 Sustainability and environmental aspects
  • 3.14.1 Sustainable practices
  • 3.14.2 Waste reduction strategies
  • 3.14.3 Energy efficiency in production
  • 3.14.4 Eco-friendly Initiatives
  • 3.14.5 Carbon footprint considerations
• 3.15 Forecast assumptions & scenario analysis (Driven by Primary Research)
  • 3.15.1 Base Case - key macro & industry variables driving CAGR
  • 3.15.2 Optimistic Scenarios - Favorable macro and industry tailwinds
  • 3.15.3 Pessimistic Scenario - Macroeconomic slowdown or industry headwinds

Chapter 4 Competitive Landscape, 2025

• 4.1 Introduction
• 4.2 Company market share analysis
  • 4.2.1 North America
  • 4.2.2 Europe
  • 4.2.3 Asia Pacific
  • 4.2.4 LATAM
  • 4.2.5 MEA
• 4.3 Competitive analysis of major market players
• 4.4 Competitive positioning matrix
• 4.5 Company Tier Benchmarking
  • 4.5.1 Tier Classification Criteria & Qualifying Thresholds
  • 4.5.2 Tier Positioning Matrix by Revenue, Geography & Innovation
• 4.6 Key developments
  • 4.6.1 Mergers & acquisitions
  • 4.6.2 Partnerships & collaborations
  • 4.6.3 New product launches
  • 4.6.4 Expansion plans and funding

Chapter 5 Market Estimates & Forecast, By Component, 2022 - 2035 ($Bn, Units)

• 5.1 Key trends
• 5.2 Hardware
  • 5.2.1 Robotic platforms & chassis
  • 5.2.2 Sensors & perception systems
  • 5.2.3 Actuators & manipulation systems
  • 5.2.4 Others
• 5.3 Software
  • 5.3.1 Robot operating systems
  • 5.3.2 Fleet management software
  • 5.3.3 Warehouse management integration
  • 5.3.4 Others
• 5.4 Services
  • 5.4.1 Professional
  • 5.4.2 Managed

Chapter 6 Market Estimates & Forecast, By Type, 2022 - 2035 ($Bn, Units)

• 6.1 Key trends
• 6.2 Automated guided vehicles
• 6.3 Autonomous mobile robots
• 6.4 Robot arms
• 6.5 Others

Chapter 7 Market Estimates & Forecast, By Application, 2022 - 2035 ($Bn, Units)

• 7.1 Key trends
• 7.2 Palletizing & de-palletizing
• 7.3 Pick & place
• 7.4 Transportation
• 7.5 Others

Chapter 8 Market Estimates & Forecast, By Payload Capacity, 2022 - 2035 ($Bn, Units)

• 8.1 Key trends
• 8.2 Low capacity (Up to 100 kg)
• 8.3 Medium capacity (100-500 kg)
• 8.4 High capacity (Above 500 kg)

Chapter 9 Market Estimates & Forecast, By End use, 2022 - 2035 ($Bn, Units)

• 9.1 Key trends
• 9.2 E-commerce
• 9.3 Healthcare
• 9.4 Retail
• 9.5 Food & beverages
• 9.6 Automotive
• 9.7 Others

Chapter 10 Market Estimates & Forecast, By Region, 2022 - 2035 ($Bn, Units)

• 10.1 Key trends
• 10.2 North America
  • 10.2.1 US
  • 10.2.2 Canada
• 10.3 Europe
  • 10.3.1 Germany
  • 10.3.2 UK
  • 10.3.3 France
  • 10.3.4 Italy
  • 10.3.5 Spain
  • 10.3.6 Russia
  • 10.3.7 Netherlands
  • 10.3.8 Sweden
  • 10.3.9 Denmark
  • 10.3.10 Poland
• 10.4 Asia Pacific
  • 10.4.1 China
  • 10.4.2 India
  • 10.4.3 Japan
  • 10.4.4 Australia
  • 10.4.5 South Korea
  • 10.4.6 Singapore
  • 10.4.7 Thailand
  • 10.4.8 Indonesia
  • 10.4.9 Vietnam
• 10.5 Latin America
  • 10.5.1 Brazil
  • 10.5.2 Mexico
  • 10.5.3 Argentina
  • 10.5.4 Colombia
• 10.6 MEA
  • 10.6.1 South Africa
  • 10.6.2 Saudi Arabia
  • 10.6.3 UAE
  • 10.6.4 Israel

Chapter 11 Company Profiles

• 11.1 Global Players
  • 11.1.1 ABB
  • 11.1.2 Amazon Robotics
  • 11.1.3 AutoStore
  • 11.1.4 Daifuku
  • 11.1.5 Honeywell
  • 11.1.6 KION/Dematic
  • 11.1.7 KUKA/Swisslog
  • 11.1.8 Omron
  • 11.1.9 Toyota/Bastian
  • 11.1.10 Yaskawa Electric
• 11.2 Regional Players
  • 11.2.1 Bastian Solutions
  • 11.2.2 Geek+
  • 11.2.3 GreyOrange
  • 11.2.4 Locus Robotics
  • 11.2.5 Vecna Robotics
• 11.3 Emerging Players
  • 11.3.1 Berkshire Grey
  • 11.3.2 Covariant
  • 11.3.3 Exotec
  • 11.3.4 River Systems
  • 11.3.5 VisionNav Robotics