The Global Autonomous Logistics Market 2027–2040: Mobile Robots, Delivery Robots, Drones and Driverless Trucks
Autonomous logistics is fast becoming one of the most important layers of the global supply chain. Warehouses, factories, distribution centres, parcel networks, food-delivery platforms and freight carriers are under sustained pressure to move goods faster and more reliably while facing labour shortages, rising wages, volatile demand and growing fulfilment complexity. Mobile robots, autonomous delivery vehicles, drones and driverless trucks answer that pressure with automation that moves. Capacity can be added in increments, layouts can be changed in weeks rather than months, and many systems can be paid for as a service rather than bought outright.
The market spans every link in the logistics chain. Inside the warehouse, automated guided vehicles (AGVs), grid-based goods-to-person robots, autonomous mobile robots (AMRs) and autonomous forklifts transport goods. They are joined by case-handling robots, mobile manipulators, truck-unloading robots and inventory-scanning robots and drones. Beyond the warehouse, China’s unmanned delivery vehicles have reached fleets of tens of thousands, and sidewalk robots deliver food and groceries through platform partnerships. Delivery drones have passed millions of commercial deliveries. Level 4 autonomous trucks now haul freight without a driver on selected US highway routes.
These technologies sit on very different maturity curves. AGVs and AMRs ship in hundreds of thousands of units a year. Mobile manipulation, robovans outside China and driverless trucking are moving from early commercial deployment to fleet scale. Indoors, technology integration and return on investment are the main challenges; outdoors, regulation is the gating factor. City road rights govern delivery vehicles, beyond-visual-line-of-sight rules govern drones, and federal and EU frameworks govern autonomous trucks. China leads in unit volume and cost, with domestic manufacturers setting global price levels in AGVs, AMRs, autonomous forklifts and robovans. North America leads in driverless trucking, sidewalk robots, truck unloading and consumer drone delivery, and Europe is strong in intralogistics systems and safety certification. Falling costs for lidar, cameras, edge compute and batteries are widening the range of tasks that can be automated economically. So are advances in AI navigation and robot foundation models.
The Global Autonomous Logistics Market 2027–2040: Mobile Robots, Delivery Robots, Drones and Driverless Trucks report provides a comprehensive analysis of the mobile robots, autonomous vehicles and drones transforming logistics, warehousing and delivery. It covers intralogistics AGVs, AGCs, grid-based goods-to-person robots, AMRs and autonomous forklifts. It also covers case-handling robots, mobile manipulators, truck unloaders and inventory robots; robovans, autonomous delivery vehicles and sidewalk robots; delivery and cargo drones; and Level 4 autonomous trucks, middle-mile and yard automation. The report combines technology benchmarking, company and deployment tracking, regulatory analysis and bottom-up forecasts. It includes 257 tables, 103 figures and 205 company profiles, with data current to October 2026.
The market spans every link in the logistics chain. Inside the warehouse, automated guided vehicles (AGVs), grid-based goods-to-person robots, autonomous mobile robots (AMRs) and autonomous forklifts transport goods. They are joined by case-handling robots, mobile manipulators, truck-unloading robots and inventory-scanning robots and drones. Beyond the warehouse, China’s unmanned delivery vehicles have reached fleets of tens of thousands, and sidewalk robots deliver food and groceries through platform partnerships. Delivery drones have passed millions of commercial deliveries. Level 4 autonomous trucks now haul freight without a driver on selected US highway routes.
These technologies sit on very different maturity curves. AGVs and AMRs ship in hundreds of thousands of units a year. Mobile manipulation, robovans outside China and driverless trucking are moving from early commercial deployment to fleet scale. Indoors, technology integration and return on investment are the main challenges; outdoors, regulation is the gating factor. City road rights govern delivery vehicles, beyond-visual-line-of-sight rules govern drones, and federal and EU frameworks govern autonomous trucks. China leads in unit volume and cost, with domestic manufacturers setting global price levels in AGVs, AMRs, autonomous forklifts and robovans. North America leads in driverless trucking, sidewalk robots, truck unloading and consumer drone delivery, and Europe is strong in intralogistics systems and safety certification. Falling costs for lidar, cameras, edge compute and batteries are widening the range of tasks that can be automated economically. So are advances in AI navigation and robot foundation models.
The Global Autonomous Logistics Market 2027–2040: Mobile Robots, Delivery Robots, Drones and Driverless Trucks report provides a comprehensive analysis of the mobile robots, autonomous vehicles and drones transforming logistics, warehousing and delivery. It covers intralogistics AGVs, AGCs, grid-based goods-to-person robots, AMRs and autonomous forklifts. It also covers case-handling robots, mobile manipulators, truck unloaders and inventory robots; robovans, autonomous delivery vehicles and sidewalk robots; delivery and cargo drones; and Level 4 autonomous trucks, middle-mile and yard automation. The report combines technology benchmarking, company and deployment tracking, regulatory analysis and bottom-up forecasts. It includes 257 tables, 103 figures and 205 company profiles, with data current to October 2026.
Report contents include:
- Market definition and taxonomy: twelve robot and vehicle categories, mapped across the logistics value chain from first mile to last metre, with autonomy levels and commercial readiness.
- Market drivers and economics: labour shortages, e-commerce growth, ROI and payback by robot type, cost per pick and per delivery, leasing and Robotics-as-a-Service, investment, funding and M&A from 2024 to 2026.
- Enabling technologies: navigation and SLAM, lidar, cameras, radar and IMUs, AI and foundation models, compute, functional safety, fleet orchestration and interoperability (VDA 5050), connectivity and teleoperation, batteries and charging.
- Intralogistics transport robots: product benchmarking by payload, speed and navigation, comparison with fixed automation, applications, and the competitive landscape.
- Mobile picking and handling: case-handling robots, mobile manipulators, truck unloading, humanoids in logistics, and inventory robots and drones.
- Ground last-mile delivery: China’s robovan boom, sidewalk robots, operating economics, and regulation by country.
- Delivery and cargo drones: aircraft designs, the FAA Part 108 BVLOS rule, regional commercialisation, case studies of Zipline, Wing and Meituan, and unit economics.
- Level 4 autonomous trucks: hub-to-hub and driver-as-a-service models, OEM platforms, deployment status, total cost of ownership analysis and timelines.
- Regulation and standards: ISO 3691-4, R15.08, the EU Machinery Regulation, the Cyber Resilience Act, AV laws, drone rules, and trade and security restrictions.
- Regional and competitive analysis: North America, Europe, China, Japan and Korea and emerging markets; market structure, leading company revenues, IPOs and strategic positioning.
- Market forecasts 2027–2040: revenue, unit sales and average selling prices by category, application group, region, end-use industry and business model, with conservative, base and optimistic scenarios.
- Future outlook: technology roadmaps, convergence trends and strategic recommendations.
- Company profiles: 205 companies across the value chain. Companies profiled include A2Z Drone Delivery, ABB Robotics, Accerion, ACSL, Addverb Technologies, Aeva, Agility Robotics, Agilox, Aitonomi (formerly TeleRetail), Amazon Prime Air, Amazon Robotics, Ambi Robotics, ANRA Technologies, Antwork Technology (Xunyi), Anyware Robotics, Applied Intuition, Apptronik, Arrive AI, Aurora Innovation, AutoStore, Aviant, Avride, Avy, BALYO, Bastian Solutions, BionicHive, BlueBotics, Boston Dynamics, Bot Auto, Brain Corp, Brightpick, Cainiao (Alibaba Group), Caja Robotics, Cartken, Clearpath Robotics / OTTO Motors, Clevon (now indiGO Europe), Coco Robotics, Corvus Robotics, Covariant, CreateAI (formerly TuSimple), Crown Equipment, Daifuku, Daimler Truck, DeepWay, Dematic, DEXA, Dexory, Dexterity, DJI, DoorDash (Dot / DoorDash Labs), Draganfly, Dronamics, DroneUp, DS Automotion, EHang, Einride, ek robotics (NEURA Mobile Robots), Elettric80, Elroy Air, Exotec, Fabric, Fernride, Flytrex, Formant, FORT Robotics, ForwardX Robotics, Fox Robotics, Gather AI, Gatik, Geek+ (Geekplus Technology), Gideon, Grenzebach, GreyOrange, HAI Robotics, Hesai Technology, Hikrobot, Hokuyo Automatic, Honeywell Intelligrated, Hyster-Yale, Hyundai Motor Group, Inceptio Technology, InOrbit, International Motors, inVia Robotics, Iplusmobot, ISEE, Isuzu Motors, JD Logistics, Jedsy, Jungheinrich, Kalmar and more.......
1. EXECUTIVE SUMMARY
1.1 Key summary
1.2 Product taxonomy and scope
1.3 Market drivers and adoption barriers
1.4 Segment highlights
1.5 Regulation and standards: the 2027 market gates
1.6 Forecast summary
1.7 Competitive landscape and investment
1.8 Key findings and strategic implications
2. INTRODUCTION AND MARKET DEFINITION
2.1 What are logistics mobile robots, autonomous vehicles and drones?
2.2 Report scope, segmentation and taxonomy
2.3 The logistics value chain and where mobile automation fits
2.4 Historical evolution
2.5 Levels of autonomy for logistics robots and vehicles
2.5.1 Autonomy framework for intralogistics robots
2.5.2 SAE J3016 levels applied to logistics vehicles
2.5.3 Drone autonomy and BVLOS operating levels
2.6 Indoor, outdoor, public-road and airspace operating domains
2.7 Commercial readiness by category, 2026
2.8 Methodology overview
2.9 Glossary of key terms
3. MARKET DRIVERS, ECONOMICS AND BUSINESS MODELS
3.1 Structural drivers
3.1.1 Labour shortages and wage inflation in warehousing
3.1.2 Driver shortages and the trucking labour crisis
3.1.3 E-commerce growth and fulfilment complexity
3.1.4 Same-day delivery and the economics of speed
3.1.5 Nearshoring, reshoring and supply-chain resilience
3.1.6 Safety and injury reduction
3.1.7 Sustainability and electrification
3.1.8 AI, software and component cost declines
3.2 Restraints and adoption barriers
3.2.1 Capital cost and the warehouse capex cycle
3.2.2 Integration complexity and brownfield sites
3.2.3 Interoperability
3.2.4 Safety certification and machinery regulation
3.2.5 Regulation for public roads and airspace
3.2.6 Public acceptance, labour relations and cybersecurity
3.2.7 ROI uncertainty and vendor failures
3.3 Impact assessment of drivers and restraints
3.4 Economics: ROI, payback and total cost of ownership
3.4.1 Capex, labour displacement and payback by robot type
3.4.2 Cost per pick in the warehouse
3.4.3 Cost per delivery in the last mile
3.4.4 Total cost of ownership
3.5 Business models
3.5.1 Robotics-as-a-Service
3.5.2 Autonomous trucking: from capacity-as-a-service to driver-as-a-service
3.5.3 Drone and robot delivery-as-a-service
3.5.4 The system integrator's role
3.6 Go-to-market and channels
3.7 Investment, funding and M&A, 2024–2026
3.8 Supply chain overview
3.9 Key takeaways
4. ENABLING TECHNOLOGIES
4.1 Technology stack overview
4.2 Navigation and guidance technologies
4.2.1 From buried wire to infrastructure-free navigation
4.2.2 Comparison of navigation methods
4.2.3 Outdoor and road navigation: HD maps versus map-light
4.2.4 Navigation used by leading products
4.3 Localisation and SLAM in depth
4.3.1 LiDAR SLAM, visual SLAM and fused approaches
4.3.2 Hard cases: dynamic warehouses, long aisles and glass
4.3.3 Navigation software and localisation vendors
4.4 Perception sensors
4.4.1 Sensor modalities compared
4.4.2 Safety-rated 2D LiDAR
4.4.3 3D LiDAR: from luxury to commodity
4.4.4 Cameras, depth sensors and the RealSense question
4.4.5 Radar, ultrasonic, IMU and odometry
4.4.6 Sensor suites on representative products
4.5 Sensor fusion, AI perception and foundation models
4.5.1 From modular pipelines to learned systems
4.5.2 Foundation models, VLAs and world models
4.5.3 Simulation and digital twins
4.6 Compute platforms
4.7 Safety systems and functional safety
4.7.1 Indoor vehicles: protective fields and ISO 3691-4
4.7.2 Road vehicles: ISO 26262, SOTIF and UL 4600
4.7.3 Drones: DO-178C, ASTM F38 and detect-and-avoid
4.8 Fleet management, orchestration and interoperability
4.8.1 Fleet managers and traffic control
4.8.2 Interoperability standards
4.8.3 WMS/WES integration and multi-vendor orchestration
4.9 Connectivity and remote operations
4.9.1 Wi-Fi and private 5G in facilities
4.9.2 Cellular, V2X and satellite for vehicles and drones
4.9.3 Teleoperation and remote assistance
4.10 Batteries
4.10.1 Chemistries by robot class
4.10.2 Battery sizing by robot type
4.11 Charging and energy management
4.11.1 Charging strategies
4.11.2 Contact, wireless and swap technologies
4.12 Drives, motors and chassis
4.12.1 Ground robot drive configurations
4.12.2 Drone propulsion, VTOL configurations and payload release
4.13 Technology benchmarking
4.14 Technology roadmap 2027–2040
5. INTRALOGISTICS TRANSPORT ROBOTS
5.1 Overview: Types of Mobile Robots in Material Handling
5.2 Automated Guided Vehicles and Carts (AGV/AGC)
5.2.1 Origins and definition
5.2.2 Types of AGV
5.2.3 Heavy-load and port AGVs
5.2.4 AGV navigation methods
5.2.5 Strengths, limitations and use in automotive and manufacturing
5.3 Grid-Based AGCs and Goods-to-Person Robots
5.3.1 From Kiva to the mass-market shelf-lifting robot
5.3.2 Amazon Robotics: the world's largest mobile robot fleet
5.3.3 Geek+, Hikrobot, Quicktron and the Chinese shelf-to-person ecosystem
5.3.4 GreyOrange, Swisslog CarryPick and Western grid-based systems
5.3.5 Cube storage robots: AutoStore and Ocado
5.4 Autonomous Mobile Robots
5.4.1 What makes a robot an AMR
5.4.2 Collaborative picking AMRs
5.4.3 Cart-transport and tugger AMRs
5.4.4 Top modules and conveyor-top AMRs
5.4.5 Sortation robots
5.4.6 Tote-to-person and hospital AMRs
5.5 Autonomous Mobile Vehicles: Autonomous Forklifts, Pallet Movers and Tuggers
5.5.1 Why the forklift is the next frontier
5.5.2 Pure-play autonomous forklift developers
5.5.3 Forklift OEMs and their automation strategies
5.5.4 Heavy-duty AMRs and tow tractors
5.6 Technology Comparison: AGV/AGC, AMR, Grid-Based AGC and Fixed Automation
5.6.1 AGV/AGC versus AMR
5.6.2 Mobile robots versus fixed automation
5.6.3 Transition of navigation technology
5.7 Pain Points and Engineering Challenges
5.7.1 Why deployments fail
5.7.2 Gap, slope and floor-condition detection
5.7.3 Mixed traffic, safety zones and standards
5.7.4 Connectivity, batteries and fleet scaling
5.7.5 Uptime, service and the RaaS model
5.8 Application Analysis
5.8.1 Overview by end market
5.8.2 E-commerce, retail and grocery
5.8.3 Third-party logistics
5.8.4 Manufacturing, electronics and new energy
5.8.5 Healthcare and pharma
5.9 Product Benchmarking
5.10 Competitive Landscape
5.10.1 Regional overview
5.10.2 Leading companies by segment
5.10.3 Revenue and scale of leading listed and filing companies
5.10.4 Installed base and market share indications
5.10.5 Strategic partnerships with forklift OEMs and navigation suppliers
5.10.6 Mergers and acquisitions
5.11 Other Goods-to-Person Approaches
5.12 Outlook and Key Takeaways
6. MOBILE PICKING, MANIPULATION AND INVENTORY ROBOTS
6.1 Forms of Mobile Picking, Manipulation and Inventory Robots
6.2 Autonomous Case-Handling Robots (ACRs)
6.2.1 Concept and architecture
6.2.2 HAI Robotics
6.2.3 Other ACR and tote-handling vendors
6.2.4 Exotec Skypod
6.2.5 ACRs versus grid AGCs and shuttle systems
6.2.6 Navigation technologies for ACRs
6.3 Mobile Manipulators for Piece Picking and Machine Tending
6.3.1 From research platform to product
6.3.2 Autonomous in-aisle piece picking
6.3.3 Industrial mobile manipulators and machine tending
6.3.4 Evolution of picking algorithms
6.3.5 Published picking performance
6.4 Truck and Container Unloading and Loading Robots
6.4.1 Why the dock is the hardest problem
6.4.2 Leading systems
6.5 Humanoid and Legged Robots in Logistics
6.5.1 Commercial status in October 2026
6.5.2 Realistic assessment of readiness
6.6 Inventory Robots and Drones
6.6.1 The case for automated inventory
6.6.2 Leading vendors
6.7 Hybrid Systems and Integration
6.7.1 Orchestrating mixed fleets
6.7.2 Case studies
6.8 Economics of Mobile Picking and Handling Robots
6.8.1 Throughput comparisons
6.8.2 Cost per pick and payback
6.9 Players
6.9.1 Case-handling and goods-to-person robot companies
6.9.2 Mobile manipulator, unloading and humanoid companies
6.10 Outlook, Challenges and Key Takeaways
6.10.1 Technology positioning
6.10.2 Challenges
7. AUTONOMOUS GROUND LAST-MILE DELIVERY
7.1 Last-mile delivery: definition, cost and volumes
7.1.1 What is last-mile delivery?
7.1.2 Why the last mile is the most expensive part of the chain
7.1.3 Why autonomous last mile?
7.1.4 Parcel and food delivery volumes
7.2 Delivery form factors
7.2.1 Overview
7.2.2 Sidewalk robots
7.2.3 Road-going low-speed delivery vehicles and robovans
7.2.4 Full-size autonomous delivery vans and pods
7.2.5 "Last metre" doorstep solutions
7.2.6 Ground versus air: comparison with delivery drones
7.3 Supporting infrastructure
7.3.1 Micro-fulfilment centres, dark stores and decentralised warehousing
7.3.2 Hubs, mobile lockers, charging and maintenance
7.3.3 Teleoperation and remote operations centres
7.4 Technologies for ground delivery vehicles
7.4.1 Sensors
7.4.2 Localisation, mapping and autonomy software
7.4.3 Connectivity, teleoperation and remote-operator ratios
7.4.4 Vehicle platforms, batteries and cost reduction
7.5 China's robovan boom
7.5.1 From pilot to industry
7.5.2 Neolix
7.5.3 Zelos
7.5.4 Platform operators and other Chinese players
7.5.5 Courier adoption, unit prices and economics
7.5.6 City road rights and operating data
7.6 United States and Europe: road-going delivery vehicles
7.6.1 Nuro: from delivery pods to autonomy licensing
7.6.2 Middle-mile and specialist road delivery players
7.6.3 DoorDash Dot and the bike-lane robot
7.7 Sidewalk delivery robots
7.7.1 Starship Technologies
7.7.2 Serve Robotics
7.7.3 Coco, Avride, Robot.com and other US operators
7.7.4 Asia: Korea, Japan and Russia
7.7.5 Product benchmarking
7.7.6 Deployment status and funding
7.8 Operating economics
7.8.1 The cost structure of a delivery robot
7.8.2 Utilisation, deliveries per day and supervision in practice
7.8.3 Comparative cost per delivery
7.9 Regulations for ground delivery robots and vehicles
7.9.1 United States: personal delivery device laws
7.9.2 China, Japan and South Korea
7.9.3 United Kingdom and Europe
7.10 Players
7.10.1 Regional distribution and what players deliver
7.10.2 Company overview table
7.11 Challenges and key takeaways
7.11.1 Challenges
7.11.2 Key takeaways
8. DELIVERY AND CARGO DRONES
8.1 Drone Logistics Overview
8.1.1 Use Cases
8.1.2 Deliveries to Date
8.1.3 Last-Mile, Mid-Mile and Long-Haul
8.2 Drone Designs
8.2.1 Multicopters
8.2.2 Fixed-Wing Aircraft
8.2.3 Hybrid VTOL: Lift+Cruise, Tilt-Rotor and Tail-Sitter
8.2.4 Payload Delivery Mechanisms
8.2.5 Payload and Range of Commercial Models
8.3 Technologies
8.3.1 Sensors and Detect-and-Avoid
8.3.2 Navigation and Autonomy
8.3.3 Operating Restrictions: Weather, Noise and Endurance
8.3.4 UTM, U-Space and Strategic Deconfliction
8.3.5 Docking, Nests and Ground Infrastructure
8.3.6 Fleet Operations and Remote-Pilot Ratios
8.4 Regulation
8.4.1 United States
8.4.2 European Union
8.4.3 United Kingdom
8.4.4 China
8.4.5 Japan, South Korea and India
8.4.6 Australia, Africa and the Middle East
8.4.7 Comparative Summary
8.5 Commercialisation Status by Region
8.5.1 United States
8.5.2 Europe and the United Kingdom
8.5.3 China
8.5.4 Japan and South Korea
8.5.5 Africa
8.5.6 India, the Middle East and Latin America
8.6 Landscape and Maturity Assessment
8.6.1 Maturity Matrix
8.7 Case Studies
8.7.1 Wing versus Zipline: Competing Approaches to US Home Delivery
8.7.2 China's Drone Logistics Race: Meituan, SF Express, JD and EHang
8.7.3 Amazon Prime Air
8.7.4 Manna in Ireland and Finland
8.7.5 Matternet and Healthcare Delivery
8.7.6 Mid-Mile and Long-Haul Cargo
8.8 Economics
8.8.1 Cost per Delivery
8.8.2 Fleet Utilisation and Site Throughput
8.8.3 Pricing Models and Infrastructure Costs
8.9 Funding and Partnerships
8.10 Barriers and Key Takeaways
9. LEVEL 4 AUTONOMOUS TRUCKS, MIDDLE-MILE AND YARD AUTOMATION
9.1 The case for automating heavy-duty trucks
9.1.1 Pain points in road freight
9.1.2 Freight market context by region
9.1.3 Why trucks first
9.2 Levels of automation and operating models
9.2.1 SAE levels applied to trucking
9.2.2 Level 2 versus Level 4 trucking
9.2.3 Operating models
9.2.4 Hub-to-hub segment economics
9.3 Business models
9.3.1 From technology developer to freight provider
9.3.2 Driver-as-a-Service: the emerging default
9.3.3 OEM strategies
9.3.4 Business models by company
9.4 Technology
9.4.1 Sensor suites
9.4.2 Redundant platforms
9.4.3 Simulation, validation and AI architecture
9.4.4 Remote assistance and operations
9.5 Regulation
9.5.1 United States: federal framework
9.5.2 United States: state laws
9.5.3 China
9.5.4 Europe
9.5.5 Japan, Korea and others
9.6 Players and market maturity
9.6.1 Industry structure after the shake-out
9.6.2 Market readiness of leading companies
9.6.3 Profiles of the leaders
9.6.4 Funding
9.6.5 Company locations
9.6.6 Deployment timeline
9.7 Deployment status, routes and safety supervision
9.7.1 United States
9.7.2 China and rest of world
9.8 Total cost of ownership analysis
9.8.1 Approach and assumptions
9.8.2 Results
9.8.3 Sensitivity
9.9 Drivers, hurdles and competitive position
9.9.1 Six key drivers
9.9.2 Remaining hurdles
9.9.3 SWOT analysis
9.9.4 Commercial readiness compared with other autonomous vehicles
9.10 Yard trucks, ports and closed-site logistics
9.10.1 Distribution and logistics yards
9.10.2 Ports and container terminals
9.10.3 Mining and industrial haulage
9.11 Timelines and outlook
9.11.1 Our view of milestones, 2027–2040
9.11.2 Ones to watch
9.11.3 Conclusion
10. REGULATION, SAFETY STANDARDS AND POLICY
10.1 Overview: four regulatory domains and the 2027 market gates
10.1.1 The four regulatory domains
10.1.2 The 2027 market gates
10.1.3 The EU Machinery Regulation and AMRs
10.1.4 UK equivalents
10.2 Industrial mobile robot safety standards
10.2.1 ISO 3691-4 and ANSI/ITSDF B56.5
10.2.2 ANSI/A3 R15.08 series
10.2.3 ISO 10218:2025 and collaborative operation
10.2.4 Functional safety, electrical and product standards
10.3 Interoperability standards
10.4 Ground delivery robots
10.4.1 United States: PDD statutes
10.4.2 China
10.4.3 Japan and South Korea
10.4.4 Europe and the UK
10.5 Road autonomous vehicles and trucks
10.5.1 United States: federal
10.5.2 United States: states
10.5.3 China
10.5.4 Europe, the UK, Japan and Korea
10.6 Drones and airspace
10.6.1 United States
10.6.2 Europe and the UK
10.6.3 China, Japan, India and Australia
10.7 Cybersecurity, data protection and AI governance
10.7.1 Product and vehicle cybersecurity
10.7.2 Data protection
10.7.3 AI governance
10.7.4 National-security restrictions on Chinese technology
10.8 Trade, tariffs and geopolitics
10.9 Insurance and liability frameworks
10.10 Regulatory readiness matrix and outlook to 2030
10.10.1 Outlook to 2030
11. REGIONAL MARKET ANALYSIS
11.1 Regional Overview: How Geography Shapes Adoption
11.1.1 Four forces that explain regional differences
11.1.2 Automation indicators
11.2 North America
11.2.1 United States
11.2.2 Canada
11.3 Europe
11.3.1 Regional characteristics and policy framework
11.3.2 Germany
11.3.3 United Kingdom
11.3.4 France, the Nordics, the Netherlands and the rest of Europe
11.4 China
11.4.1 Market characteristics
11.4.2 Policy support
11.4.3 Adoption by segment
11.5 Japan
11.5.1 The "2024 problem" and the logistics labour crisis
11.5.2 Adoption by segment and leading players
11.6 South Korea
11.7 India and Southeast Asia
11.7.1 India
11.7.2 Southeast Asia
11.8 Middle East
11.9 Latin America
11.10 Africa
11.11 Comparative Assessment
11.11.1 Government programmes
11.11.2 Leading players by region
11.11.3 Regional maturity by segment
11.11.4 Labour context across regions
12. COMPETITIVE LANDSCAPE, STRATEGY AND INVESTMENT
12.1 Market Structure by Segment
12.1.1 A fragmented market with concentrated pockets
12.1.2 In-house versus merchant supply
12.2 Strategic Groupings
12.2.1 Competitive positioning
12.2.2 Competitive dynamics within the principal segments
12.3 Financial Benchmarking of Leading Listed Companies
12.3.1 Revenues and profitability
12.3.2 What the numbers show
12.4 Mergers and Acquisitions, 2020–2026
12.4.1 Patterns in deal activity
12.5 Investment and Funding
12.5.1 Funding cycle, 2021–2026
12.5.2 IPO pipeline
12.6 Strategic Partnerships
12.7 Competitive Strategies
12.7.1 Vertical integration
12.7.2 Robots-as-a-service and outcome-based pricing
12.7.3 Ecosystems, interoperability and software platforms
12.7.4 Price competition from China
12.7.5 Summary of strategic archetypes
12.8 Ones to Watch
13. MARKET FORECASTS 2027–2040
13.1 Forecast scope, definitions and methodology
13.2 Global market revenue and unit sales, 2025–2040
13.3 Scenario analysis
13.4 Forecast by application group
13.5 Forecast by robot and vehicle category
13.6 Intralogistics transport robots
13.7 Mobile picking and handling robots
13.8 Last-mile delivery robots, vehicles and drones
13.9 Level 4 autonomous trucks and middle-mile freight
13.10 Forecast by region
13.11 Intralogistics and picking robots by end-use industry
13.12 Business model mix: equipment sales, leasing and Robotics-as-a-Service
13.13 Captive deployments, sensitivities and forecast risks
14. FUTURE OUTLOOK AND TECHNOLOGY ROADMAP
14.1 Outlook: From Islands of Automation to Autonomous Logistics Networks
14.2 Technology Roadmap by Segment
14.2.1 Roadmap overview
14.2.2 Key milestones
14.2.3 Cost curves and the economics of scale
14.3 Convergence Themes
14.3.1 Humanoids and AMRs
14.3.2 Robovans, drones and the "mothership" model
14.3.3 Autonomous trucks and automated hubs
14.3.4 Lights-out warehouses
14.4 Impact on Labour and Jobs
14.4.1 Scale of exposure
14.4.2 Displacement, augmentation and new roles
14.4.3 Policy and social licence
14.5 Scenarios to 2040
14.6 Opportunities for Suppliers
14.6.1 Enabling technologies
14.7 Strategic Recommendations
14.7.1 For technology vendors
14.7.2 For investors
14.7.3 For logistics operators and shippers
15. COMPANY PROFILES (205 COMPANY PROFILES)
16. APPENDIX: RESEARCH METHODOLOGY
16.1 Research approach
16.2 Market definition and segmentation
16.3 Forecast methodology
16.4 Limitations
17. REFERENCES
1.1 Key summary
1.2 Product taxonomy and scope
1.3 Market drivers and adoption barriers
1.4 Segment highlights
1.5 Regulation and standards: the 2027 market gates
1.6 Forecast summary
1.7 Competitive landscape and investment
1.8 Key findings and strategic implications
2. INTRODUCTION AND MARKET DEFINITION
2.1 What are logistics mobile robots, autonomous vehicles and drones?
2.2 Report scope, segmentation and taxonomy
2.3 The logistics value chain and where mobile automation fits
2.4 Historical evolution
2.5 Levels of autonomy for logistics robots and vehicles
2.5.1 Autonomy framework for intralogistics robots
2.5.2 SAE J3016 levels applied to logistics vehicles
2.5.3 Drone autonomy and BVLOS operating levels
2.6 Indoor, outdoor, public-road and airspace operating domains
2.7 Commercial readiness by category, 2026
2.8 Methodology overview
2.9 Glossary of key terms
3. MARKET DRIVERS, ECONOMICS AND BUSINESS MODELS
3.1 Structural drivers
3.1.1 Labour shortages and wage inflation in warehousing
3.1.2 Driver shortages and the trucking labour crisis
3.1.3 E-commerce growth and fulfilment complexity
3.1.4 Same-day delivery and the economics of speed
3.1.5 Nearshoring, reshoring and supply-chain resilience
3.1.6 Safety and injury reduction
3.1.7 Sustainability and electrification
3.1.8 AI, software and component cost declines
3.2 Restraints and adoption barriers
3.2.1 Capital cost and the warehouse capex cycle
3.2.2 Integration complexity and brownfield sites
3.2.3 Interoperability
3.2.4 Safety certification and machinery regulation
3.2.5 Regulation for public roads and airspace
3.2.6 Public acceptance, labour relations and cybersecurity
3.2.7 ROI uncertainty and vendor failures
3.3 Impact assessment of drivers and restraints
3.4 Economics: ROI, payback and total cost of ownership
3.4.1 Capex, labour displacement and payback by robot type
3.4.2 Cost per pick in the warehouse
3.4.3 Cost per delivery in the last mile
3.4.4 Total cost of ownership
3.5 Business models
3.5.1 Robotics-as-a-Service
3.5.2 Autonomous trucking: from capacity-as-a-service to driver-as-a-service
3.5.3 Drone and robot delivery-as-a-service
3.5.4 The system integrator's role
3.6 Go-to-market and channels
3.7 Investment, funding and M&A, 2024–2026
3.8 Supply chain overview
3.9 Key takeaways
4. ENABLING TECHNOLOGIES
4.1 Technology stack overview
4.2 Navigation and guidance technologies
4.2.1 From buried wire to infrastructure-free navigation
4.2.2 Comparison of navigation methods
4.2.3 Outdoor and road navigation: HD maps versus map-light
4.2.4 Navigation used by leading products
4.3 Localisation and SLAM in depth
4.3.1 LiDAR SLAM, visual SLAM and fused approaches
4.3.2 Hard cases: dynamic warehouses, long aisles and glass
4.3.3 Navigation software and localisation vendors
4.4 Perception sensors
4.4.1 Sensor modalities compared
4.4.2 Safety-rated 2D LiDAR
4.4.3 3D LiDAR: from luxury to commodity
4.4.4 Cameras, depth sensors and the RealSense question
4.4.5 Radar, ultrasonic, IMU and odometry
4.4.6 Sensor suites on representative products
4.5 Sensor fusion, AI perception and foundation models
4.5.1 From modular pipelines to learned systems
4.5.2 Foundation models, VLAs and world models
4.5.3 Simulation and digital twins
4.6 Compute platforms
4.7 Safety systems and functional safety
4.7.1 Indoor vehicles: protective fields and ISO 3691-4
4.7.2 Road vehicles: ISO 26262, SOTIF and UL 4600
4.7.3 Drones: DO-178C, ASTM F38 and detect-and-avoid
4.8 Fleet management, orchestration and interoperability
4.8.1 Fleet managers and traffic control
4.8.2 Interoperability standards
4.8.3 WMS/WES integration and multi-vendor orchestration
4.9 Connectivity and remote operations
4.9.1 Wi-Fi and private 5G in facilities
4.9.2 Cellular, V2X and satellite for vehicles and drones
4.9.3 Teleoperation and remote assistance
4.10 Batteries
4.10.1 Chemistries by robot class
4.10.2 Battery sizing by robot type
4.11 Charging and energy management
4.11.1 Charging strategies
4.11.2 Contact, wireless and swap technologies
4.12 Drives, motors and chassis
4.12.1 Ground robot drive configurations
4.12.2 Drone propulsion, VTOL configurations and payload release
4.13 Technology benchmarking
4.14 Technology roadmap 2027–2040
5. INTRALOGISTICS TRANSPORT ROBOTS
5.1 Overview: Types of Mobile Robots in Material Handling
5.2 Automated Guided Vehicles and Carts (AGV/AGC)
5.2.1 Origins and definition
5.2.2 Types of AGV
5.2.3 Heavy-load and port AGVs
5.2.4 AGV navigation methods
5.2.5 Strengths, limitations and use in automotive and manufacturing
5.3 Grid-Based AGCs and Goods-to-Person Robots
5.3.1 From Kiva to the mass-market shelf-lifting robot
5.3.2 Amazon Robotics: the world's largest mobile robot fleet
5.3.3 Geek+, Hikrobot, Quicktron and the Chinese shelf-to-person ecosystem
5.3.4 GreyOrange, Swisslog CarryPick and Western grid-based systems
5.3.5 Cube storage robots: AutoStore and Ocado
5.4 Autonomous Mobile Robots
5.4.1 What makes a robot an AMR
5.4.2 Collaborative picking AMRs
5.4.3 Cart-transport and tugger AMRs
5.4.4 Top modules and conveyor-top AMRs
5.4.5 Sortation robots
5.4.6 Tote-to-person and hospital AMRs
5.5 Autonomous Mobile Vehicles: Autonomous Forklifts, Pallet Movers and Tuggers
5.5.1 Why the forklift is the next frontier
5.5.2 Pure-play autonomous forklift developers
5.5.3 Forklift OEMs and their automation strategies
5.5.4 Heavy-duty AMRs and tow tractors
5.6 Technology Comparison: AGV/AGC, AMR, Grid-Based AGC and Fixed Automation
5.6.1 AGV/AGC versus AMR
5.6.2 Mobile robots versus fixed automation
5.6.3 Transition of navigation technology
5.7 Pain Points and Engineering Challenges
5.7.1 Why deployments fail
5.7.2 Gap, slope and floor-condition detection
5.7.3 Mixed traffic, safety zones and standards
5.7.4 Connectivity, batteries and fleet scaling
5.7.5 Uptime, service and the RaaS model
5.8 Application Analysis
5.8.1 Overview by end market
5.8.2 E-commerce, retail and grocery
5.8.3 Third-party logistics
5.8.4 Manufacturing, electronics and new energy
5.8.5 Healthcare and pharma
5.9 Product Benchmarking
5.10 Competitive Landscape
5.10.1 Regional overview
5.10.2 Leading companies by segment
5.10.3 Revenue and scale of leading listed and filing companies
5.10.4 Installed base and market share indications
5.10.5 Strategic partnerships with forklift OEMs and navigation suppliers
5.10.6 Mergers and acquisitions
5.11 Other Goods-to-Person Approaches
5.12 Outlook and Key Takeaways
6. MOBILE PICKING, MANIPULATION AND INVENTORY ROBOTS
6.1 Forms of Mobile Picking, Manipulation and Inventory Robots
6.2 Autonomous Case-Handling Robots (ACRs)
6.2.1 Concept and architecture
6.2.2 HAI Robotics
6.2.3 Other ACR and tote-handling vendors
6.2.4 Exotec Skypod
6.2.5 ACRs versus grid AGCs and shuttle systems
6.2.6 Navigation technologies for ACRs
6.3 Mobile Manipulators for Piece Picking and Machine Tending
6.3.1 From research platform to product
6.3.2 Autonomous in-aisle piece picking
6.3.3 Industrial mobile manipulators and machine tending
6.3.4 Evolution of picking algorithms
6.3.5 Published picking performance
6.4 Truck and Container Unloading and Loading Robots
6.4.1 Why the dock is the hardest problem
6.4.2 Leading systems
6.5 Humanoid and Legged Robots in Logistics
6.5.1 Commercial status in October 2026
6.5.2 Realistic assessment of readiness
6.6 Inventory Robots and Drones
6.6.1 The case for automated inventory
6.6.2 Leading vendors
6.7 Hybrid Systems and Integration
6.7.1 Orchestrating mixed fleets
6.7.2 Case studies
6.8 Economics of Mobile Picking and Handling Robots
6.8.1 Throughput comparisons
6.8.2 Cost per pick and payback
6.9 Players
6.9.1 Case-handling and goods-to-person robot companies
6.9.2 Mobile manipulator, unloading and humanoid companies
6.10 Outlook, Challenges and Key Takeaways
6.10.1 Technology positioning
6.10.2 Challenges
7. AUTONOMOUS GROUND LAST-MILE DELIVERY
7.1 Last-mile delivery: definition, cost and volumes
7.1.1 What is last-mile delivery?
7.1.2 Why the last mile is the most expensive part of the chain
7.1.3 Why autonomous last mile?
7.1.4 Parcel and food delivery volumes
7.2 Delivery form factors
7.2.1 Overview
7.2.2 Sidewalk robots
7.2.3 Road-going low-speed delivery vehicles and robovans
7.2.4 Full-size autonomous delivery vans and pods
7.2.5 "Last metre" doorstep solutions
7.2.6 Ground versus air: comparison with delivery drones
7.3 Supporting infrastructure
7.3.1 Micro-fulfilment centres, dark stores and decentralised warehousing
7.3.2 Hubs, mobile lockers, charging and maintenance
7.3.3 Teleoperation and remote operations centres
7.4 Technologies for ground delivery vehicles
7.4.1 Sensors
7.4.2 Localisation, mapping and autonomy software
7.4.3 Connectivity, teleoperation and remote-operator ratios
7.4.4 Vehicle platforms, batteries and cost reduction
7.5 China's robovan boom
7.5.1 From pilot to industry
7.5.2 Neolix
7.5.3 Zelos
7.5.4 Platform operators and other Chinese players
7.5.5 Courier adoption, unit prices and economics
7.5.6 City road rights and operating data
7.6 United States and Europe: road-going delivery vehicles
7.6.1 Nuro: from delivery pods to autonomy licensing
7.6.2 Middle-mile and specialist road delivery players
7.6.3 DoorDash Dot and the bike-lane robot
7.7 Sidewalk delivery robots
7.7.1 Starship Technologies
7.7.2 Serve Robotics
7.7.3 Coco, Avride, Robot.com and other US operators
7.7.4 Asia: Korea, Japan and Russia
7.7.5 Product benchmarking
7.7.6 Deployment status and funding
7.8 Operating economics
7.8.1 The cost structure of a delivery robot
7.8.2 Utilisation, deliveries per day and supervision in practice
7.8.3 Comparative cost per delivery
7.9 Regulations for ground delivery robots and vehicles
7.9.1 United States: personal delivery device laws
7.9.2 China, Japan and South Korea
7.9.3 United Kingdom and Europe
7.10 Players
7.10.1 Regional distribution and what players deliver
7.10.2 Company overview table
7.11 Challenges and key takeaways
7.11.1 Challenges
7.11.2 Key takeaways
8. DELIVERY AND CARGO DRONES
8.1 Drone Logistics Overview
8.1.1 Use Cases
8.1.2 Deliveries to Date
8.1.3 Last-Mile, Mid-Mile and Long-Haul
8.2 Drone Designs
8.2.1 Multicopters
8.2.2 Fixed-Wing Aircraft
8.2.3 Hybrid VTOL: Lift+Cruise, Tilt-Rotor and Tail-Sitter
8.2.4 Payload Delivery Mechanisms
8.2.5 Payload and Range of Commercial Models
8.3 Technologies
8.3.1 Sensors and Detect-and-Avoid
8.3.2 Navigation and Autonomy
8.3.3 Operating Restrictions: Weather, Noise and Endurance
8.3.4 UTM, U-Space and Strategic Deconfliction
8.3.5 Docking, Nests and Ground Infrastructure
8.3.6 Fleet Operations and Remote-Pilot Ratios
8.4 Regulation
8.4.1 United States
8.4.2 European Union
8.4.3 United Kingdom
8.4.4 China
8.4.5 Japan, South Korea and India
8.4.6 Australia, Africa and the Middle East
8.4.7 Comparative Summary
8.5 Commercialisation Status by Region
8.5.1 United States
8.5.2 Europe and the United Kingdom
8.5.3 China
8.5.4 Japan and South Korea
8.5.5 Africa
8.5.6 India, the Middle East and Latin America
8.6 Landscape and Maturity Assessment
8.6.1 Maturity Matrix
8.7 Case Studies
8.7.1 Wing versus Zipline: Competing Approaches to US Home Delivery
8.7.2 China's Drone Logistics Race: Meituan, SF Express, JD and EHang
8.7.3 Amazon Prime Air
8.7.4 Manna in Ireland and Finland
8.7.5 Matternet and Healthcare Delivery
8.7.6 Mid-Mile and Long-Haul Cargo
8.8 Economics
8.8.1 Cost per Delivery
8.8.2 Fleet Utilisation and Site Throughput
8.8.3 Pricing Models and Infrastructure Costs
8.9 Funding and Partnerships
8.10 Barriers and Key Takeaways
9. LEVEL 4 AUTONOMOUS TRUCKS, MIDDLE-MILE AND YARD AUTOMATION
9.1 The case for automating heavy-duty trucks
9.1.1 Pain points in road freight
9.1.2 Freight market context by region
9.1.3 Why trucks first
9.2 Levels of automation and operating models
9.2.1 SAE levels applied to trucking
9.2.2 Level 2 versus Level 4 trucking
9.2.3 Operating models
9.2.4 Hub-to-hub segment economics
9.3 Business models
9.3.1 From technology developer to freight provider
9.3.2 Driver-as-a-Service: the emerging default
9.3.3 OEM strategies
9.3.4 Business models by company
9.4 Technology
9.4.1 Sensor suites
9.4.2 Redundant platforms
9.4.3 Simulation, validation and AI architecture
9.4.4 Remote assistance and operations
9.5 Regulation
9.5.1 United States: federal framework
9.5.2 United States: state laws
9.5.3 China
9.5.4 Europe
9.5.5 Japan, Korea and others
9.6 Players and market maturity
9.6.1 Industry structure after the shake-out
9.6.2 Market readiness of leading companies
9.6.3 Profiles of the leaders
9.6.4 Funding
9.6.5 Company locations
9.6.6 Deployment timeline
9.7 Deployment status, routes and safety supervision
9.7.1 United States
9.7.2 China and rest of world
9.8 Total cost of ownership analysis
9.8.1 Approach and assumptions
9.8.2 Results
9.8.3 Sensitivity
9.9 Drivers, hurdles and competitive position
9.9.1 Six key drivers
9.9.2 Remaining hurdles
9.9.3 SWOT analysis
9.9.4 Commercial readiness compared with other autonomous vehicles
9.10 Yard trucks, ports and closed-site logistics
9.10.1 Distribution and logistics yards
9.10.2 Ports and container terminals
9.10.3 Mining and industrial haulage
9.11 Timelines and outlook
9.11.1 Our view of milestones, 2027–2040
9.11.2 Ones to watch
9.11.3 Conclusion
10. REGULATION, SAFETY STANDARDS AND POLICY
10.1 Overview: four regulatory domains and the 2027 market gates
10.1.1 The four regulatory domains
10.1.2 The 2027 market gates
10.1.3 The EU Machinery Regulation and AMRs
10.1.4 UK equivalents
10.2 Industrial mobile robot safety standards
10.2.1 ISO 3691-4 and ANSI/ITSDF B56.5
10.2.2 ANSI/A3 R15.08 series
10.2.3 ISO 10218:2025 and collaborative operation
10.2.4 Functional safety, electrical and product standards
10.3 Interoperability standards
10.4 Ground delivery robots
10.4.1 United States: PDD statutes
10.4.2 China
10.4.3 Japan and South Korea
10.4.4 Europe and the UK
10.5 Road autonomous vehicles and trucks
10.5.1 United States: federal
10.5.2 United States: states
10.5.3 China
10.5.4 Europe, the UK, Japan and Korea
10.6 Drones and airspace
10.6.1 United States
10.6.2 Europe and the UK
10.6.3 China, Japan, India and Australia
10.7 Cybersecurity, data protection and AI governance
10.7.1 Product and vehicle cybersecurity
10.7.2 Data protection
10.7.3 AI governance
10.7.4 National-security restrictions on Chinese technology
10.8 Trade, tariffs and geopolitics
10.9 Insurance and liability frameworks
10.10 Regulatory readiness matrix and outlook to 2030
10.10.1 Outlook to 2030
11. REGIONAL MARKET ANALYSIS
11.1 Regional Overview: How Geography Shapes Adoption
11.1.1 Four forces that explain regional differences
11.1.2 Automation indicators
11.2 North America
11.2.1 United States
11.2.2 Canada
11.3 Europe
11.3.1 Regional characteristics and policy framework
11.3.2 Germany
11.3.3 United Kingdom
11.3.4 France, the Nordics, the Netherlands and the rest of Europe
11.4 China
11.4.1 Market characteristics
11.4.2 Policy support
11.4.3 Adoption by segment
11.5 Japan
11.5.1 The "2024 problem" and the logistics labour crisis
11.5.2 Adoption by segment and leading players
11.6 South Korea
11.7 India and Southeast Asia
11.7.1 India
11.7.2 Southeast Asia
11.8 Middle East
11.9 Latin America
11.10 Africa
11.11 Comparative Assessment
11.11.1 Government programmes
11.11.2 Leading players by region
11.11.3 Regional maturity by segment
11.11.4 Labour context across regions
12. COMPETITIVE LANDSCAPE, STRATEGY AND INVESTMENT
12.1 Market Structure by Segment
12.1.1 A fragmented market with concentrated pockets
12.1.2 In-house versus merchant supply
12.2 Strategic Groupings
12.2.1 Competitive positioning
12.2.2 Competitive dynamics within the principal segments
12.3 Financial Benchmarking of Leading Listed Companies
12.3.1 Revenues and profitability
12.3.2 What the numbers show
12.4 Mergers and Acquisitions, 2020–2026
12.4.1 Patterns in deal activity
12.5 Investment and Funding
12.5.1 Funding cycle, 2021–2026
12.5.2 IPO pipeline
12.6 Strategic Partnerships
12.7 Competitive Strategies
12.7.1 Vertical integration
12.7.2 Robots-as-a-service and outcome-based pricing
12.7.3 Ecosystems, interoperability and software platforms
12.7.4 Price competition from China
12.7.5 Summary of strategic archetypes
12.8 Ones to Watch
13. MARKET FORECASTS 2027–2040
13.1 Forecast scope, definitions and methodology
13.2 Global market revenue and unit sales, 2025–2040
13.3 Scenario analysis
13.4 Forecast by application group
13.5 Forecast by robot and vehicle category
13.6 Intralogistics transport robots
13.7 Mobile picking and handling robots
13.8 Last-mile delivery robots, vehicles and drones
13.9 Level 4 autonomous trucks and middle-mile freight
13.10 Forecast by region
13.11 Intralogistics and picking robots by end-use industry
13.12 Business model mix: equipment sales, leasing and Robotics-as-a-Service
13.13 Captive deployments, sensitivities and forecast risks
14. FUTURE OUTLOOK AND TECHNOLOGY ROADMAP
14.1 Outlook: From Islands of Automation to Autonomous Logistics Networks
14.2 Technology Roadmap by Segment
14.2.1 Roadmap overview
14.2.2 Key milestones
14.2.3 Cost curves and the economics of scale
14.3 Convergence Themes
14.3.1 Humanoids and AMRs
14.3.2 Robovans, drones and the "mothership" model
14.3.3 Autonomous trucks and automated hubs
14.3.4 Lights-out warehouses
14.4 Impact on Labour and Jobs
14.4.1 Scale of exposure
14.4.2 Displacement, augmentation and new roles
14.4.3 Policy and social licence
14.5 Scenarios to 2040
14.6 Opportunities for Suppliers
14.6.1 Enabling technologies
14.7 Strategic Recommendations
14.7.1 For technology vendors
14.7.2 For investors
14.7.3 For logistics operators and shippers
15. COMPANY PROFILES (205 COMPANY PROFILES)
16. APPENDIX: RESEARCH METHODOLOGY
16.1 Research approach
16.2 Market definition and segmentation
16.3 Forecast methodology
16.4 Limitations
17. REFERENCES
LIST OF TABLES
Table 1. Headline market metrics, 2026–2040 (base case)
Table 2. Summary of categories: environment, maturity and leading companies (2026)
Table 3. Major market drivers and restraints
Table 4. Revenue forecast by category, 2026–2040 (US$ million, base case)
Table 5. Unit sales forecast by category, 2026–2040 (units, base case)
Table 6. Fixed automation versus mobile automation in logistics
Table 7. Product categories in scope — definitions, payloads, environments and leading examples
Table 8. Mapping mobile robot and autonomous vehicle categories to logistics value-chain stages
Table 9. Selected historical milestones by segment
Table 10. Autonomy framework for intralogistics mobile robots
Table 11. SAE J3016 driving automation levels and their relevance to logistics vehicles
Table 12. Operational autonomy levels for delivery and cargo drones
Table 13. Comparison of operating domains for logistics mobile robots, AVs and drones
Table 14. Technology and commercial readiness by category, 2026
Table 15. Key definitions and conventions used in this report
Table 16. Glossary of key terms
Table 17. Summary of structural market drivers
Table 18. Labour-market indicators for warehousing and freight transport
Table 19. Summary of market restraints and adoption barriers
Table 20. Selected vendor failures, exits and distressed transactions, 2023–2026
Table 21. Impact assessment of drivers and restraints over time (–3 strong negative to +3 strong positive)
Table 22. Indicative economics and payback by robot and vehicle type, 2026 (US/Western Europe)
Table 23. Productivity and estimated cost per order line by fulfilment method (US, 2026)
Table 24. Total cost of ownership components for mobile robot and autonomous vehicle deployments
Table 25. Comparison of business models in logistics mobile automation
Table 26. Indicative pricing structures by segment, 2026
Table 27. Go-to-market channels and representative partnerships
Table 28. Selected major funding rounds and listings, 2024–2026
Table 29. Selected mergers, acquisitions and strategic transactions, 2023–2026
Table 30. Mobile robot component supply chain
Table 31. Where engineering effort concentrates in the stack, by robot category
Table 32. Comparison of navigation and guidance technologies
Table 33. Map strategies for outdoor and on-road logistics autonomy
Table 34. Navigation approaches used by representative logistics robots and vehicles
Table 35. Localisation challenges in logistics environments and common mitigations
Table 36. Selected navigation and localisation software vendors for logistics vehicles
Table 37. Perception sensor modalities for logistics robots and vehicles
Table 38. Representative safety-rated 2D LiDAR scanners used on AGVs and AMRs
Table 39. Representative 3D LiDAR and depth sensors used in logistics robots and vehicles
Table 40. Sensor suites on representative logistics robots, vehicles and drones
Table 41. AI models and simulation platforms relevant to logistics robotics
Table 42. Compute platforms for logistics robots, autonomous vehicles and drones
Table 43. Safety standards and frameworks by robot category
Table 44. Interoperability standards and frameworks for multi-vendor robot fleets
Table 45. Fleet management and multi-vendor orchestration platforms
Table 46. Indicative network requirements for remote operations of logistics robots and vehicles
Table 47. Battery chemistries for logistics robots, vehicles and drones
Table 48. Typical battery sizing by logistics robot and vehicle type
Table 49. Charging and energy-replenishment approaches for logistics robots and vehicles
Table 50. Ground robot drive and chassis configurations
Table 51. Delivery drone propulsion configurations and payload-release methods
Table 52. Technology roadmap for logistics mobile robots, autonomous vehicles and drones, 2027–2040
Table 53. Working definitions of intralogistics transport robot categories
Table 54. Main types of automated guided vehicle
Table 55. Representative AGV-based automated container terminals
Table 56. AGV guidance and navigation methods compared
Table 57. AGV and AMR use cases in automotive and battery manufacturing
Table 58. Leading grid-based AGC / shelf-to-person robot product families
Table 59. Amazon Robotics fleet: principal mobile and handling robots
Table 60. Collaborative picking and picking-assist AMR platforms
Table 61. Selected cart-transport, tugger and top-module AMR platforms
Table 62. Robotic sortation systems compared with fixed sortation
Table 63. Forklift OEM automation portfolios
Table 64. Representative autonomous forklift, pallet-mover and tugger products
Table 65. AGV/AGC versus AMR: comparison of key attributes
Table 66. Mobile robots versus fixed automation: deployment, cost and performance characteristics
Table 67. Generations of mobile robot navigation technology
Table 68. Pain points of intralogistics mobile robots and engineering responses
Table 69. Key safety standards for intralogistics mobile robots
Table 70. Applications of intralogistics transport robots by end market
Table 71. Benchmark of selected intralogistics transport robots
Table 72. Selected intralogistics transport robot companies by region and category
Table 73. Leading AGV suppliers and their positioning
Table 74. Leading grid-based AGC and cube-storage robot suppliers
Table 75. Leading AMR suppliers and positioning
Table 76. Leading autonomous forklift and AMV developers
Table 77. Reported revenues of selected listed and IPO-filing intralogistics robot companies
Table 78. Strategic partnerships between autonomy developers and forklift OEMs / logistics users
Table 79. Selected mergers and acquisitions in intralogistics mobile robotics
Table 80. Alternative goods-to-person architectures and their status
Table 81. Classes of mobile picking, manipulation and inventory robots
Table 82. HAI Robotics HaiPick product family (principal configurations)
Table 83. Selected case-handling and tote-retrieval robot products
Table 84. Comparison of goods-to-person storage technologies (typical ranges)
Table 85. Navigation and positioning technologies used by case-handling robots
Table 86. Representative mobile manipulator products for logistics and industrial use
Table 87. Generations of robotic grasping and picking algorithms
Table 88. Robot foundation-model and AI-manipulation companies relevant to logistics
Table 89. Publicly stated performance indicators for picking and handling robots
Table 90. Truck and container unloading and loading robots
Table 91. Humanoid robots in logistics: programmes and deployment status (October 2026)
Table 92. Humanoids versus purpose-built robots for warehouse tote handling
Table 93. Inventory robot and drone vendors
Table 94. Comparison of automated inventory approaches
Table 95. Selected deployments of case-handling, picking and unloading robots
Table 96. Indicative fully loaded cost per pick by configuration (US/Western Europe, 2026)
Table 97. Payback drivers for mobile picking, unloading and inventory robots
Table 98. Case-handling robot and mobile goods-to-person companies
Table 99. Mobile manipulator, truck-unloading and logistics humanoid companies
Table 100. Safety standards relevant to mobile manipulators, case-handling robots and humanoids
Table 101. Key challenges by category
Table 102. Indicative cost structure of conventional last-mile delivery (2025–2026)
Table 103. Main last-mile volume pools relevant to autonomous ground delivery
Table 104. Autonomous ground delivery form factors — typical specifications (2026)
Table 105. "Last metre" delivery approaches
Table 106. Ground delivery systems versus delivery drones — performance comparison
Table 107. Ground delivery systems versus delivery drones — regulatory and commercial comparison
Table 108. Supporting infrastructure requirements by form factor
Table 109. Sensor suites of representative autonomous ground delivery platforms
Table 110. Localisation and autonomy approaches in ground delivery
Table 111. Remote supervision models in autonomous ground delivery (indicative)
Table 112. Major Chinese unmanned delivery vehicle companies (October 2026)
Table 113. Representative Chinese robovan products and prices
Table 114. Robovan adoption by Chinese express and logistics companies (2025–2026)
Table 115. Selected Chinese city regimes for unmanned delivery vehicles (2025–2026)
Table 116. US and European road-going autonomous delivery players (October 2026)
Table 117. Benchmarking of leading sidewalk and small road delivery robots (2026)
Table 118. Sidewalk delivery robot deployment status (October 2026)
Table 119. Major funding events in autonomous ground delivery, 2025–2026
Table 120. Illustrative annual cost model for a sidewalk delivery robot (US$, Future Markets estimates)
Table 121. Key operating metrics by delivery model (2025–2026, indicative)
Table 122. Typical provisions of US state personal delivery device (PDD) laws
Table 123. Regulatory status of ground delivery robots and vehicles by country (October 2026)
Table 124. What autonomous ground delivery players deliver today (2026)
Table 125. Autonomous ground last-mile delivery companies (October 2026)
Table 126. Key challenges for autonomous ground delivery and mitigation approaches
Table 127. Principal use cases for delivery and cargo drones
Table 128. Cumulative drone deliveries reported by leading operators (latest disclosure)
Table 129. Comparison of last-mile, mid-mile and long-haul drone logistics
Table 130. Drone logistics operating scenarios
Table 131. Comparison of delivery drone configurations
Table 132. Payload delivery mechanisms
Table 133. Specifications of selected delivery and cargo drones
Table 134. Sensing and detect-and-avoid technologies used in delivery drones
Table 135. Operating constraints for delivery drones and mitigation approaches
Table 136. UTM and airspace integration initiatives relevant to drone delivery
Table 137. Evolution of drone delivery staffing models
Table 138. US regulatory status of leading drone delivery operators
Table 139. Key provisions of the proposed FAA Part 108 BVLOS rule
Table 140. Drone delivery regulatory status by country/region (October 2026)
Table 141. Principal US drone delivery operators and partners (2026)
Table 142. Drone delivery activity in Europe and the UK
Table 143. Leading Chinese drone logistics operators
Table 144. Drone delivery activity in Asia-Pacific (excluding China)
Table 145. Zipline and other drone delivery operations in Africa
Table 146. Drone delivery activity in India, the Middle East and Latin America
Table 147. Delivery and cargo drone company landscape
Table 148. Wing and Zipline compared
Table 149. China's leading drone logistics players compared
Table 150. Mid-mile and long-haul cargo drone programmes
Table 151. Estimated cost per last-mile delivery, van versus drone (US$, 2026)
Table 152. Disclosed utilisation and throughput indicators
Table 153. Drone delivery pricing models
Table 154. Indicative infrastructure requirements and costs by model
Table 155. Selected funding rounds and strategic partnerships in drone delivery
Table 156. Barriers to drone delivery and their trajectory
Table 157. Trucking pain points and how Level 4 autonomy addresses them
Table 158. Road freight context for autonomous trucking by region
Table 159. SAE levels of driving automation applied to heavy trucks
Table 160. Indicative segment characteristics of a hub-to-hub autonomous lane
Table 161. Business model options for autonomous trucking developers
Table 162. Truck OEM autonomy strategies and partnerships (October 2026)
Table 163. Business and operating models of leading autonomous freight companies
Table 164. Sensor suites and compute of leading autonomous truck developers
Table 165. OEM autonomy-ready redundant truck platforms
Table 166. Operational infrastructure required for driverless trucking
Table 167. Key US federal instruments affecting autonomous trucks (October 2026)
Table 168. State regulatory position for driverless heavy trucks (October 2026)
Table 169. International regulatory frameworks for L4 autonomous trucks
Table 170. Notable exits and pivots in autonomous trucking
Table 171. Market readiness of autonomous truck and freight autonomy companies (October 2026)
Table 172. Selected autonomous trucking funding and capital-markets events, 2024–2026
Table 173. Headquarters and operating bases of autonomous freight companies
Table 174. Autonomous truck deployment status, routes and safety supervision (October 2026)
Table 175. Principal US autonomous trucking corridors
Table 176. Selected autonomous truck deployments outside the United States
Table 177. TCO model assumptions — US Class 8 long-haul tractor
Table 178. Per-mile TCO comparison — human-driven vs L4 DaaS (US$ per mile)
Table 179. Sensitivity of early-phase L4 TCO to key variables
Table 180. Key drivers and hurdles for heavy-duty L4 trucks — impact assessment
Table 181. SWOT analysis — heavy-duty Level 4 autonomous trucks
Table 182. Yard, port and closed-site autonomous freight vehicle providers
Table 183. Future Markets view of autonomous trucking milestones, 2027–2040
Table 184. Ones to watch in autonomous trucking
Table 185. The four regulatory domains for logistics mobile robots, autonomous vehicles and drones
Table 186. Key regulatory "gates", September 2026 – August 2028
Table 187. EU Machinery Regulation 2023/1230 — key changes for mobile robots versus Directive 2006/42/EC
Table 188. Safety and product standards for industrial mobile robots
Table 189. Typical AMR safety functions and target performance levels
Table 190. Interoperability standards for mobile robot fleets
Table 191. Representative US state personal delivery device laws
Table 192. International frameworks for ground delivery robots
Table 193. United States framework for autonomous delivery vehicles and trucks (October 2026)
Table 194. Road AV and autonomous truck regulation by country (October 2026)
Table 195. US regulatory pathways for drone delivery operations
Table 196. Drone delivery regulation by country (October 2026)
Table 197. US national-security measures affecting Chinese robotics, AV and drone technology
Table 198. Cybersecurity, data protection and AI governance instruments
Table 199. Trade and tariff measures affecting logistics robots, AVs and drones (2018–2026)
Table 200. Liability and insurance frameworks by segment and jurisdiction
Table 201. Expected regulatory milestones, 2026–2030
Table 202. Regional comparison of adoption drivers for logistics mobile robots, autonomous vehicles and drones (2026)
Table 203. Industrial robot installations and robot density, selected countries (latest IFR data)
Table 204. Selected notable US deployments of logistics autonomy (to October 2026)
Table 205. European country profiles for logistics mobile autonomy (2026)
Table 206. China's principal policy instruments for logistics robots, unmanned vehicles and drones
Table 207. Leading Chinese players in logistics robots, unmanned vehicles and drones
Table 208. Japan's responses to the logistics "2024 problem" relevant to autonomy
Table 209. South Korea: key policies and players in logistics autonomy
Table 210. India and Southeast Asia: leading players and representative deployments
Table 211. Representative deployments in the Middle East, Latin America and Africa
Table 212. Government programmes and regulatory milestones supporting logistics autonomy, by region
Table 213. Leading players by region and segment (2026)
Table 214. Labour context and its implications for logistics automation, by region
Table 215. Competitive structure by segment (October 2026)
Table 216. Captive, hybrid and merchant supply models in logistics automation
Table 217. Strategic groups in logistics mobile autonomy
Table 218. Revenue and profitability of leading listed companies in logistics automation and autonomy (latest fiscal year)
Table 219. Key mergers, acquisitions and take-privates in logistics mobile autonomy, 2020–2026
Table 220. Notable failures, shutdowns and restructurings, 2022–2026
Table 221. Major disclosed funding rounds in logistics mobile autonomy, 2021–2026
Table 222. IPO and listing pipeline for logistics mobile autonomy companies (October 2026)
Table 223. Strategic partnerships shaping the logistics autonomy market (selected, to October 2026)
Table 224. Chinese versus Western vendors: competitive positioning in warehouse robotics
Table 225. Competitive strategy archetypes in logistics mobile autonomy
Table 226. Ones to watch, 2027–2028
Table 227. Base-year assumptions and key forecast drivers by category
Table 228. Global market revenue and unit sales for logistics mobile robots, autonomous vehicles and drones, 2025–2040 (base case)
Table 229. Global market revenue by scenario, 2025–2040 (US$ billion)
Table 230. Global revenue by application group, 2025–2040 (US$ billion)
Table 231. Global unit sales by application group, 2025–2040 (thousand units)
Table 232. Global revenue by category, 2026–2040 (US$ million)
Table 233. Global unit sales by category, 2026–2040 (units)
Table 234. Average selling price assumptions by category, 2026–2040 (US$ per unit)
Table 235. Intralogistics transport robots: revenue by category, 2025–2040 (US$ million)
Table 236. Intralogistics transport robots: unit sales by category, 2025–2040 (units)
Table 237. Mobile picking and handling robots: revenue by category, 2025–2040 (US$ million)
Table 238. Mobile picking and handling robots: unit sales by category, 2025–2040 (units)
Table 239. Last-mile delivery robots, vehicles and drones: revenue by category, 2025–2040 (US$ million)
Table 240. Last-mile delivery robots, vehicles and drones: unit sales by category, 2025–2040 (units)
Table 241. Last-mile delivery revenue by end application, 2025–2040 (US$ million)
Table 242. Level 4 autonomous trucks and middle-mile freight: revenue by category, 2025–2040 (US$ million)
Table 243. Level 4 autonomous trucks and middle-mile freight: unit sales by category, 2025–2040 (units)
Table 244. Autonomous freight: annual deliveries and installed fleet, 2025–2040 (units)
Table 245. Global revenue by region, 2025–2040 (US$ million)
Table 246. Revenue by region and application group, 2030 and 2040 (US$ million)
Table 247. Regional revenue share by category, 2026 and 2040
Table 248. Intralogistics and mobile picking robot revenue by end-use industry, 2025–2040 (US$ million)
Table 249. Share of revenue delivered through RaaS, leasing and as-a-service contracts, 2026–2040
Table 250. Key forecast sensitivities and risks
Table 251. Technology and commercial roadmap by segment, 2027–2040
Table 252. Convergence themes in logistics autonomy, 2027–2040
Table 253. Expected labour impact of logistics autonomy by occupation, 2027–2040
Table 254. Scenario comparison: key drivers and outcomes (qualitative)
Table 255. Opportunities for component, software and service suppliers
Table 256. Strategic recommendations by stakeholder and horizon
Table 257. Forecast categories and application groups
Table 1. Headline market metrics, 2026–2040 (base case)
Table 2. Summary of categories: environment, maturity and leading companies (2026)
Table 3. Major market drivers and restraints
Table 4. Revenue forecast by category, 2026–2040 (US$ million, base case)
Table 5. Unit sales forecast by category, 2026–2040 (units, base case)
Table 6. Fixed automation versus mobile automation in logistics
Table 7. Product categories in scope — definitions, payloads, environments and leading examples
Table 8. Mapping mobile robot and autonomous vehicle categories to logistics value-chain stages
Table 9. Selected historical milestones by segment
Table 10. Autonomy framework for intralogistics mobile robots
Table 11. SAE J3016 driving automation levels and their relevance to logistics vehicles
Table 12. Operational autonomy levels for delivery and cargo drones
Table 13. Comparison of operating domains for logistics mobile robots, AVs and drones
Table 14. Technology and commercial readiness by category, 2026
Table 15. Key definitions and conventions used in this report
Table 16. Glossary of key terms
Table 17. Summary of structural market drivers
Table 18. Labour-market indicators for warehousing and freight transport
Table 19. Summary of market restraints and adoption barriers
Table 20. Selected vendor failures, exits and distressed transactions, 2023–2026
Table 21. Impact assessment of drivers and restraints over time (–3 strong negative to +3 strong positive)
Table 22. Indicative economics and payback by robot and vehicle type, 2026 (US/Western Europe)
Table 23. Productivity and estimated cost per order line by fulfilment method (US, 2026)
Table 24. Total cost of ownership components for mobile robot and autonomous vehicle deployments
Table 25. Comparison of business models in logistics mobile automation
Table 26. Indicative pricing structures by segment, 2026
Table 27. Go-to-market channels and representative partnerships
Table 28. Selected major funding rounds and listings, 2024–2026
Table 29. Selected mergers, acquisitions and strategic transactions, 2023–2026
Table 30. Mobile robot component supply chain
Table 31. Where engineering effort concentrates in the stack, by robot category
Table 32. Comparison of navigation and guidance technologies
Table 33. Map strategies for outdoor and on-road logistics autonomy
Table 34. Navigation approaches used by representative logistics robots and vehicles
Table 35. Localisation challenges in logistics environments and common mitigations
Table 36. Selected navigation and localisation software vendors for logistics vehicles
Table 37. Perception sensor modalities for logistics robots and vehicles
Table 38. Representative safety-rated 2D LiDAR scanners used on AGVs and AMRs
Table 39. Representative 3D LiDAR and depth sensors used in logistics robots and vehicles
Table 40. Sensor suites on representative logistics robots, vehicles and drones
Table 41. AI models and simulation platforms relevant to logistics robotics
Table 42. Compute platforms for logistics robots, autonomous vehicles and drones
Table 43. Safety standards and frameworks by robot category
Table 44. Interoperability standards and frameworks for multi-vendor robot fleets
Table 45. Fleet management and multi-vendor orchestration platforms
Table 46. Indicative network requirements for remote operations of logistics robots and vehicles
Table 47. Battery chemistries for logistics robots, vehicles and drones
Table 48. Typical battery sizing by logistics robot and vehicle type
Table 49. Charging and energy-replenishment approaches for logistics robots and vehicles
Table 50. Ground robot drive and chassis configurations
Table 51. Delivery drone propulsion configurations and payload-release methods
Table 52. Technology roadmap for logistics mobile robots, autonomous vehicles and drones, 2027–2040
Table 53. Working definitions of intralogistics transport robot categories
Table 54. Main types of automated guided vehicle
Table 55. Representative AGV-based automated container terminals
Table 56. AGV guidance and navigation methods compared
Table 57. AGV and AMR use cases in automotive and battery manufacturing
Table 58. Leading grid-based AGC / shelf-to-person robot product families
Table 59. Amazon Robotics fleet: principal mobile and handling robots
Table 60. Collaborative picking and picking-assist AMR platforms
Table 61. Selected cart-transport, tugger and top-module AMR platforms
Table 62. Robotic sortation systems compared with fixed sortation
Table 63. Forklift OEM automation portfolios
Table 64. Representative autonomous forklift, pallet-mover and tugger products
Table 65. AGV/AGC versus AMR: comparison of key attributes
Table 66. Mobile robots versus fixed automation: deployment, cost and performance characteristics
Table 67. Generations of mobile robot navigation technology
Table 68. Pain points of intralogistics mobile robots and engineering responses
Table 69. Key safety standards for intralogistics mobile robots
Table 70. Applications of intralogistics transport robots by end market
Table 71. Benchmark of selected intralogistics transport robots
Table 72. Selected intralogistics transport robot companies by region and category
Table 73. Leading AGV suppliers and their positioning
Table 74. Leading grid-based AGC and cube-storage robot suppliers
Table 75. Leading AMR suppliers and positioning
Table 76. Leading autonomous forklift and AMV developers
Table 77. Reported revenues of selected listed and IPO-filing intralogistics robot companies
Table 78. Strategic partnerships between autonomy developers and forklift OEMs / logistics users
Table 79. Selected mergers and acquisitions in intralogistics mobile robotics
Table 80. Alternative goods-to-person architectures and their status
Table 81. Classes of mobile picking, manipulation and inventory robots
Table 82. HAI Robotics HaiPick product family (principal configurations)
Table 83. Selected case-handling and tote-retrieval robot products
Table 84. Comparison of goods-to-person storage technologies (typical ranges)
Table 85. Navigation and positioning technologies used by case-handling robots
Table 86. Representative mobile manipulator products for logistics and industrial use
Table 87. Generations of robotic grasping and picking algorithms
Table 88. Robot foundation-model and AI-manipulation companies relevant to logistics
Table 89. Publicly stated performance indicators for picking and handling robots
Table 90. Truck and container unloading and loading robots
Table 91. Humanoid robots in logistics: programmes and deployment status (October 2026)
Table 92. Humanoids versus purpose-built robots for warehouse tote handling
Table 93. Inventory robot and drone vendors
Table 94. Comparison of automated inventory approaches
Table 95. Selected deployments of case-handling, picking and unloading robots
Table 96. Indicative fully loaded cost per pick by configuration (US/Western Europe, 2026)
Table 97. Payback drivers for mobile picking, unloading and inventory robots
Table 98. Case-handling robot and mobile goods-to-person companies
Table 99. Mobile manipulator, truck-unloading and logistics humanoid companies
Table 100. Safety standards relevant to mobile manipulators, case-handling robots and humanoids
Table 101. Key challenges by category
Table 102. Indicative cost structure of conventional last-mile delivery (2025–2026)
Table 103. Main last-mile volume pools relevant to autonomous ground delivery
Table 104. Autonomous ground delivery form factors — typical specifications (2026)
Table 105. "Last metre" delivery approaches
Table 106. Ground delivery systems versus delivery drones — performance comparison
Table 107. Ground delivery systems versus delivery drones — regulatory and commercial comparison
Table 108. Supporting infrastructure requirements by form factor
Table 109. Sensor suites of representative autonomous ground delivery platforms
Table 110. Localisation and autonomy approaches in ground delivery
Table 111. Remote supervision models in autonomous ground delivery (indicative)
Table 112. Major Chinese unmanned delivery vehicle companies (October 2026)
Table 113. Representative Chinese robovan products and prices
Table 114. Robovan adoption by Chinese express and logistics companies (2025–2026)
Table 115. Selected Chinese city regimes for unmanned delivery vehicles (2025–2026)
Table 116. US and European road-going autonomous delivery players (October 2026)
Table 117. Benchmarking of leading sidewalk and small road delivery robots (2026)
Table 118. Sidewalk delivery robot deployment status (October 2026)
Table 119. Major funding events in autonomous ground delivery, 2025–2026
Table 120. Illustrative annual cost model for a sidewalk delivery robot (US$, Future Markets estimates)
Table 121. Key operating metrics by delivery model (2025–2026, indicative)
Table 122. Typical provisions of US state personal delivery device (PDD) laws
Table 123. Regulatory status of ground delivery robots and vehicles by country (October 2026)
Table 124. What autonomous ground delivery players deliver today (2026)
Table 125. Autonomous ground last-mile delivery companies (October 2026)
Table 126. Key challenges for autonomous ground delivery and mitigation approaches
Table 127. Principal use cases for delivery and cargo drones
Table 128. Cumulative drone deliveries reported by leading operators (latest disclosure)
Table 129. Comparison of last-mile, mid-mile and long-haul drone logistics
Table 130. Drone logistics operating scenarios
Table 131. Comparison of delivery drone configurations
Table 132. Payload delivery mechanisms
Table 133. Specifications of selected delivery and cargo drones
Table 134. Sensing and detect-and-avoid technologies used in delivery drones
Table 135. Operating constraints for delivery drones and mitigation approaches
Table 136. UTM and airspace integration initiatives relevant to drone delivery
Table 137. Evolution of drone delivery staffing models
Table 138. US regulatory status of leading drone delivery operators
Table 139. Key provisions of the proposed FAA Part 108 BVLOS rule
Table 140. Drone delivery regulatory status by country/region (October 2026)
Table 141. Principal US drone delivery operators and partners (2026)
Table 142. Drone delivery activity in Europe and the UK
Table 143. Leading Chinese drone logistics operators
Table 144. Drone delivery activity in Asia-Pacific (excluding China)
Table 145. Zipline and other drone delivery operations in Africa
Table 146. Drone delivery activity in India, the Middle East and Latin America
Table 147. Delivery and cargo drone company landscape
Table 148. Wing and Zipline compared
Table 149. China's leading drone logistics players compared
Table 150. Mid-mile and long-haul cargo drone programmes
Table 151. Estimated cost per last-mile delivery, van versus drone (US$, 2026)
Table 152. Disclosed utilisation and throughput indicators
Table 153. Drone delivery pricing models
Table 154. Indicative infrastructure requirements and costs by model
Table 155. Selected funding rounds and strategic partnerships in drone delivery
Table 156. Barriers to drone delivery and their trajectory
Table 157. Trucking pain points and how Level 4 autonomy addresses them
Table 158. Road freight context for autonomous trucking by region
Table 159. SAE levels of driving automation applied to heavy trucks
Table 160. Indicative segment characteristics of a hub-to-hub autonomous lane
Table 161. Business model options for autonomous trucking developers
Table 162. Truck OEM autonomy strategies and partnerships (October 2026)
Table 163. Business and operating models of leading autonomous freight companies
Table 164. Sensor suites and compute of leading autonomous truck developers
Table 165. OEM autonomy-ready redundant truck platforms
Table 166. Operational infrastructure required for driverless trucking
Table 167. Key US federal instruments affecting autonomous trucks (October 2026)
Table 168. State regulatory position for driverless heavy trucks (October 2026)
Table 169. International regulatory frameworks for L4 autonomous trucks
Table 170. Notable exits and pivots in autonomous trucking
Table 171. Market readiness of autonomous truck and freight autonomy companies (October 2026)
Table 172. Selected autonomous trucking funding and capital-markets events, 2024–2026
Table 173. Headquarters and operating bases of autonomous freight companies
Table 174. Autonomous truck deployment status, routes and safety supervision (October 2026)
Table 175. Principal US autonomous trucking corridors
Table 176. Selected autonomous truck deployments outside the United States
Table 177. TCO model assumptions — US Class 8 long-haul tractor
Table 178. Per-mile TCO comparison — human-driven vs L4 DaaS (US$ per mile)
Table 179. Sensitivity of early-phase L4 TCO to key variables
Table 180. Key drivers and hurdles for heavy-duty L4 trucks — impact assessment
Table 181. SWOT analysis — heavy-duty Level 4 autonomous trucks
Table 182. Yard, port and closed-site autonomous freight vehicle providers
Table 183. Future Markets view of autonomous trucking milestones, 2027–2040
Table 184. Ones to watch in autonomous trucking
Table 185. The four regulatory domains for logistics mobile robots, autonomous vehicles and drones
Table 186. Key regulatory "gates", September 2026 – August 2028
Table 187. EU Machinery Regulation 2023/1230 — key changes for mobile robots versus Directive 2006/42/EC
Table 188. Safety and product standards for industrial mobile robots
Table 189. Typical AMR safety functions and target performance levels
Table 190. Interoperability standards for mobile robot fleets
Table 191. Representative US state personal delivery device laws
Table 192. International frameworks for ground delivery robots
Table 193. United States framework for autonomous delivery vehicles and trucks (October 2026)
Table 194. Road AV and autonomous truck regulation by country (October 2026)
Table 195. US regulatory pathways for drone delivery operations
Table 196. Drone delivery regulation by country (October 2026)
Table 197. US national-security measures affecting Chinese robotics, AV and drone technology
Table 198. Cybersecurity, data protection and AI governance instruments
Table 199. Trade and tariff measures affecting logistics robots, AVs and drones (2018–2026)
Table 200. Liability and insurance frameworks by segment and jurisdiction
Table 201. Expected regulatory milestones, 2026–2030
Table 202. Regional comparison of adoption drivers for logistics mobile robots, autonomous vehicles and drones (2026)
Table 203. Industrial robot installations and robot density, selected countries (latest IFR data)
Table 204. Selected notable US deployments of logistics autonomy (to October 2026)
Table 205. European country profiles for logistics mobile autonomy (2026)
Table 206. China's principal policy instruments for logistics robots, unmanned vehicles and drones
Table 207. Leading Chinese players in logistics robots, unmanned vehicles and drones
Table 208. Japan's responses to the logistics "2024 problem" relevant to autonomy
Table 209. South Korea: key policies and players in logistics autonomy
Table 210. India and Southeast Asia: leading players and representative deployments
Table 211. Representative deployments in the Middle East, Latin America and Africa
Table 212. Government programmes and regulatory milestones supporting logistics autonomy, by region
Table 213. Leading players by region and segment (2026)
Table 214. Labour context and its implications for logistics automation, by region
Table 215. Competitive structure by segment (October 2026)
Table 216. Captive, hybrid and merchant supply models in logistics automation
Table 217. Strategic groups in logistics mobile autonomy
Table 218. Revenue and profitability of leading listed companies in logistics automation and autonomy (latest fiscal year)
Table 219. Key mergers, acquisitions and take-privates in logistics mobile autonomy, 2020–2026
Table 220. Notable failures, shutdowns and restructurings, 2022–2026
Table 221. Major disclosed funding rounds in logistics mobile autonomy, 2021–2026
Table 222. IPO and listing pipeline for logistics mobile autonomy companies (October 2026)
Table 223. Strategic partnerships shaping the logistics autonomy market (selected, to October 2026)
Table 224. Chinese versus Western vendors: competitive positioning in warehouse robotics
Table 225. Competitive strategy archetypes in logistics mobile autonomy
Table 226. Ones to watch, 2027–2028
Table 227. Base-year assumptions and key forecast drivers by category
Table 228. Global market revenue and unit sales for logistics mobile robots, autonomous vehicles and drones, 2025–2040 (base case)
Table 229. Global market revenue by scenario, 2025–2040 (US$ billion)
Table 230. Global revenue by application group, 2025–2040 (US$ billion)
Table 231. Global unit sales by application group, 2025–2040 (thousand units)
Table 232. Global revenue by category, 2026–2040 (US$ million)
Table 233. Global unit sales by category, 2026–2040 (units)
Table 234. Average selling price assumptions by category, 2026–2040 (US$ per unit)
Table 235. Intralogistics transport robots: revenue by category, 2025–2040 (US$ million)
Table 236. Intralogistics transport robots: unit sales by category, 2025–2040 (units)
Table 237. Mobile picking and handling robots: revenue by category, 2025–2040 (US$ million)
Table 238. Mobile picking and handling robots: unit sales by category, 2025–2040 (units)
Table 239. Last-mile delivery robots, vehicles and drones: revenue by category, 2025–2040 (US$ million)
Table 240. Last-mile delivery robots, vehicles and drones: unit sales by category, 2025–2040 (units)
Table 241. Last-mile delivery revenue by end application, 2025–2040 (US$ million)
Table 242. Level 4 autonomous trucks and middle-mile freight: revenue by category, 2025–2040 (US$ million)
Table 243. Level 4 autonomous trucks and middle-mile freight: unit sales by category, 2025–2040 (units)
Table 244. Autonomous freight: annual deliveries and installed fleet, 2025–2040 (units)
Table 245. Global revenue by region, 2025–2040 (US$ million)
Table 246. Revenue by region and application group, 2030 and 2040 (US$ million)
Table 247. Regional revenue share by category, 2026 and 2040
Table 248. Intralogistics and mobile picking robot revenue by end-use industry, 2025–2040 (US$ million)
Table 249. Share of revenue delivered through RaaS, leasing and as-a-service contracts, 2026–2040
Table 250. Key forecast sensitivities and risks
Table 251. Technology and commercial roadmap by segment, 2027–2040
Table 252. Convergence themes in logistics autonomy, 2027–2040
Table 253. Expected labour impact of logistics autonomy by occupation, 2027–2040
Table 254. Scenario comparison: key drivers and outcomes (qualitative)
Table 255. Opportunities for component, software and service suppliers
Table 256. Strategic recommendations by stakeholder and horizon
Table 257. Forecast categories and application groups
LIST OF FIGURES
Figure 1. Global market revenue by application group, 2026–2040 (US$ billion)
Figure 2. Taxonomy of logistics mobile robots, autonomous vehicles and drones covered in this report
Figure 3. Global unit sales by application group, 2026–2040 (thousand units)
Figure 4. Global market revenue by scenario, 2026–2040 (US$ billion)
Figure 5. Taxonomy of logistics mobile robots, autonomous vehicles and drones covered in this report
Figure 6. The logistics value chain from first mile to last metre
Figure 7. Milestones in logistics mobile robots, autonomous vehicles and drones, 1953–2026
Figure 8. Readiness heatmap by category, 2026
Figure 9. E-commerce share of total US retail sales, 2019–2026 (approximate annual averages; 2026 = Q2)
Figure 10. Strength of drivers and restraints by segment group (1 = weak, 5 = very strong)
Figure 11. Estimated fully loaded cost per order line by fulfilment method, US, 2026 (mid-point estimates)
Figure 12. Estimated cost per delivery by mode, small on-demand orders (US$)
Figure 13. Illustrative cumulative net cash flow, 50-robot AMR deployment — purchase versus RaaS (US$ million)
Figure 14. Largest disclosed funding rounds and listing proceeds in logistics mobile automation, 2025–2026 (US$ million)
Figure 15. Estimated hardware bill of materials for a typical indoor AMR, 2026 (% of hardware cost)
Figure 16. Technology stack of a logistics mobile robot, autonomous vehicle or drone
Figure 17. Evolution of navigation and guidance technologies for logistics vehicles
Figure 18. Approximate price of representative 3D LiDAR units for autonomous navigation, 2007–2026 (US$)
Figure 19. Vendor-quoted AI performance of selected robot compute modules (TOPS/TFLOPS, mixed precision)
Figure 20. Typical battery pack energy by logistics robot/vehicle class (midpoint, kWh)
Figure 21. Positioning of charging approaches by infrastructure cost and achievable fleet uptime
Figure 22. Technology benchmarking heatmap by robot category (1 = low, 5 = high)
Figure 23. Payload versus maximum speed for representative logistics robots and vehicles (log scales)
Figure 24. Taxonomy of intralogistics transport robots
Figure 25. Key milestones in intralogistics transport robots
Figure 26. Technology maturity versus remaining opportunity by intralogistics robot category
Figure 27. Intralogistics automation technologies scored against buyer criteria (5 = most favourable)
Figure 28. Technology evolution towards fully autonomous intralogistics robots
Figure 29. Current adoption depth and remaining automation potential by end market (qualitative score, 1–5)
Figure 30. Payload versus maximum speed of selected intralogistics transport robots
Figure 31. Latest annual revenues of selected intralogistics robot companies (US$ million)
Figure 32. Revenue of Geek+ and Symbotic, 2022–2025 (US$ million)
Figure 33. Geek+ revenue by geography, 2025
Figure 34. Cumulative mobile robots deployed or delivered, selected merchant suppliers (company-reported, units)
Figure 35. Taxonomy of mobile picking, manipulation and inventory robots in logistics
Figure 36. HAI Robotics revenue and net loss, 2023–2025 (RMB million)
Figure 37. Typical maximum storage or reach height by goods-to-person technology (m)
Figure 38. Milestones in logistics mobile manipulation and picking robots
Figure 39. Stated maximum unloading throughput versus manual benchmark (cases per hour)
Figure 40. Readiness of humanoid robots for logistics tasks versus purpose-built alternatives (1 = low, 5 = high)
Figure 41. Representative hybrid robotic fulfilment flow
Figure 42. Typical sustained throughput by picking configuration (picks or lines per hour, midpoint estimates)
Figure 43. Selected funding rounds and capital raises, 2021–2026 (US$ million)
Figure 44. Technology maturity versus near-term commercial opportunity for mobile picking and handling robots
Figure 45. Where autonomous ground delivery fits in the fulfilment chain
Figure 46. China express parcel volume, 2020–2025 (billion parcels)
Figure 47. Taxonomy of autonomous ground last-mile delivery systems
Figure 48. Relative strengths of autonomous delivery form factors (1 = weak, 5 = strong)
Figure 49. Key milestones in China's unmanned delivery vehicle industry
Figure 50. Fleet growth of China's two leading robovan companies, 2023–2026 (vehicles, approximate)
Figure 51. Share of China's unmanned delivery vehicle market (2025–2026, approximate)
Figure 52. Disclosed funding of selected autonomous ground delivery companies (US$ million, approximate)
Figure 53. Estimated cost per on-demand delivery by delivery model, Western markets (US$, 2026)
Figure 54. Estimated cost per parcel, China trunk-to-station leg (RMB per parcel)
Figure 55. Positioning of leading autonomous ground delivery players (2026)
Figure 56. Cumulative deliveries reported by leading drone delivery operators (thousands, latest disclosure to 2026)
Figure 57. Taxonomy of delivery and cargo drone configurations
Figure 58. Payload versus range of selected delivery and cargo drones (log scales; range is total one-way range or twice the service radius)
Figure 59. Key regulatory and commercial milestones in drone delivery
Figure 60. Maturity matrix for drone logistics segments and leading players
Figure 61. Estimated cost per delivery by cost element, van versus drone at low and high density (US$, mid-point estimates)
Figure 62. Disclosed cumulative funding of independent drone delivery and cargo companies (US$ million, estimated, to October 2026)
Figure 63. Taxonomy of autonomous trucking operating models
Figure 64. Hub-to-hub autonomous freight flow
Figure 65. Estimated cumulative capital raised by autonomous freight developers (US$ million, to October 2026)
Figure 66. Milestones in autonomous trucking commercialisation
Figure 67. Per-mile cost of a US Class 8 long-haul truck: human-driven vs Level 4 (US$ per mile)
Figure 68. Early-phase L4 cost per mile vs annual utilisation at three autonomy-fee levels (US$ per mile)
Figure 69. Commercial readiness comparison of autonomous vehicle segments
Figure 70. Technology maturity vs logistics opportunity for autonomous freight segments
Figure 71. Expected autonomous trucking milestones, 2027–2040
Figure 72. Major regulatory milestones for logistics robots, AVs and drones, 2023–2027
Figure 73. EU conformity route for an AMR placed on the market after 20 January 2027
Figure 74. Drone regulation timeline, 2016–2028
Figure 75. Regulatory readiness matrix by country and segment, October 2026 (1 = no pathway, 5 = scalable framework)
Figure 76. Industrial robot installations by country, 2025 (units)
Figure 77. Regional regulatory and policy milestones for logistics autonomy, 2021–2027
Figure 78. Regional maturity heatmap by logistics autonomy segment (2026)
Figure 79. Competitive positioning of leading warehouse automation vendors (Future Markets assessment)
Figure 80. Competitive positioning of outdoor autonomy operators (Future Markets assessment)
Figure 81. Latest annual revenue of leading logistics automation companies (US$ million, converted at approximate 2025 average rates)
Figure 82. Largest disclosed funding rounds in logistics mobile autonomy and adjacent physical AI, 2021–2026 (US$ million)
Figure 83. Selected listings and listing milestones, 2024–2026
Figure 84. Global market revenue, 2025–2040 (US$ billion, base case)
Figure 85. Global market revenue by scenario, 2025–2040 (US$ billion)
Figure 86. Global revenue by application group, 2026–2040 (US$ billion)
Figure 87. Revenue share by application group, 2026 and 2040
Figure 88. Global revenue by category, 2040 (US$ billion, base case)
Figure 89. Revenue mix by category, 2026 vs 2040
Figure 90. Intralogistics transport robots: revenue by category, 2025–2040 (US$ billion)
Figure 91. Intralogistics transport robots: unit sales by category, 2025–2040 (thousand units)
Figure 92. Mobile picking and handling robots: revenue by category, 2025–2040 (US$ billion)
Figure 93. Mobile picking and handling robots: unit sales by category, 2025–2040 (thousand units)
Figure 94. Last-mile delivery robots, vehicles and drones: revenue by category, 2025–2040 (US$ billion)
Figure 95. Last-mile delivery robots, vehicles and drones: unit sales by category, 2025–2040 (thousand units)
Figure 96. Level 4 autonomous trucks and middle-mile freight: revenue by category, 2025–2040 (US$ billion)
Figure 97. Level 4 autonomous trucks and middle-mile freight: unit sales by category, 2025–2040 (thousand units)
Figure 98. Global revenue by region, 2026–2040 (US$ billion)
Figure 99. Regional revenue share, 2026 vs 2040 (%)
Figure 100. Intralogistics and mobile picking robot revenue by end-use industry, 2026 and 2040 (US$ billion)
Figure 101. Announced targets and expected milestones for logistics autonomy, 2027–2040
Figure 102. The emerging autonomous freight chain
Figure 103. Supplier opportunity matrix: maturity versus opportunity (Future Markets assessment)
Figure 1. Global market revenue by application group, 2026–2040 (US$ billion)
Figure 2. Taxonomy of logistics mobile robots, autonomous vehicles and drones covered in this report
Figure 3. Global unit sales by application group, 2026–2040 (thousand units)
Figure 4. Global market revenue by scenario, 2026–2040 (US$ billion)
Figure 5. Taxonomy of logistics mobile robots, autonomous vehicles and drones covered in this report
Figure 6. The logistics value chain from first mile to last metre
Figure 7. Milestones in logistics mobile robots, autonomous vehicles and drones, 1953–2026
Figure 8. Readiness heatmap by category, 2026
Figure 9. E-commerce share of total US retail sales, 2019–2026 (approximate annual averages; 2026 = Q2)
Figure 10. Strength of drivers and restraints by segment group (1 = weak, 5 = very strong)
Figure 11. Estimated fully loaded cost per order line by fulfilment method, US, 2026 (mid-point estimates)
Figure 12. Estimated cost per delivery by mode, small on-demand orders (US$)
Figure 13. Illustrative cumulative net cash flow, 50-robot AMR deployment — purchase versus RaaS (US$ million)
Figure 14. Largest disclosed funding rounds and listing proceeds in logistics mobile automation, 2025–2026 (US$ million)
Figure 15. Estimated hardware bill of materials for a typical indoor AMR, 2026 (% of hardware cost)
Figure 16. Technology stack of a logistics mobile robot, autonomous vehicle or drone
Figure 17. Evolution of navigation and guidance technologies for logistics vehicles
Figure 18. Approximate price of representative 3D LiDAR units for autonomous navigation, 2007–2026 (US$)
Figure 19. Vendor-quoted AI performance of selected robot compute modules (TOPS/TFLOPS, mixed precision)
Figure 20. Typical battery pack energy by logistics robot/vehicle class (midpoint, kWh)
Figure 21. Positioning of charging approaches by infrastructure cost and achievable fleet uptime
Figure 22. Technology benchmarking heatmap by robot category (1 = low, 5 = high)
Figure 23. Payload versus maximum speed for representative logistics robots and vehicles (log scales)
Figure 24. Taxonomy of intralogistics transport robots
Figure 25. Key milestones in intralogistics transport robots
Figure 26. Technology maturity versus remaining opportunity by intralogistics robot category
Figure 27. Intralogistics automation technologies scored against buyer criteria (5 = most favourable)
Figure 28. Technology evolution towards fully autonomous intralogistics robots
Figure 29. Current adoption depth and remaining automation potential by end market (qualitative score, 1–5)
Figure 30. Payload versus maximum speed of selected intralogistics transport robots
Figure 31. Latest annual revenues of selected intralogistics robot companies (US$ million)
Figure 32. Revenue of Geek+ and Symbotic, 2022–2025 (US$ million)
Figure 33. Geek+ revenue by geography, 2025
Figure 34. Cumulative mobile robots deployed or delivered, selected merchant suppliers (company-reported, units)
Figure 35. Taxonomy of mobile picking, manipulation and inventory robots in logistics
Figure 36. HAI Robotics revenue and net loss, 2023–2025 (RMB million)
Figure 37. Typical maximum storage or reach height by goods-to-person technology (m)
Figure 38. Milestones in logistics mobile manipulation and picking robots
Figure 39. Stated maximum unloading throughput versus manual benchmark (cases per hour)
Figure 40. Readiness of humanoid robots for logistics tasks versus purpose-built alternatives (1 = low, 5 = high)
Figure 41. Representative hybrid robotic fulfilment flow
Figure 42. Typical sustained throughput by picking configuration (picks or lines per hour, midpoint estimates)
Figure 43. Selected funding rounds and capital raises, 2021–2026 (US$ million)
Figure 44. Technology maturity versus near-term commercial opportunity for mobile picking and handling robots
Figure 45. Where autonomous ground delivery fits in the fulfilment chain
Figure 46. China express parcel volume, 2020–2025 (billion parcels)
Figure 47. Taxonomy of autonomous ground last-mile delivery systems
Figure 48. Relative strengths of autonomous delivery form factors (1 = weak, 5 = strong)
Figure 49. Key milestones in China's unmanned delivery vehicle industry
Figure 50. Fleet growth of China's two leading robovan companies, 2023–2026 (vehicles, approximate)
Figure 51. Share of China's unmanned delivery vehicle market (2025–2026, approximate)
Figure 52. Disclosed funding of selected autonomous ground delivery companies (US$ million, approximate)
Figure 53. Estimated cost per on-demand delivery by delivery model, Western markets (US$, 2026)
Figure 54. Estimated cost per parcel, China trunk-to-station leg (RMB per parcel)
Figure 55. Positioning of leading autonomous ground delivery players (2026)
Figure 56. Cumulative deliveries reported by leading drone delivery operators (thousands, latest disclosure to 2026)
Figure 57. Taxonomy of delivery and cargo drone configurations
Figure 58. Payload versus range of selected delivery and cargo drones (log scales; range is total one-way range or twice the service radius)
Figure 59. Key regulatory and commercial milestones in drone delivery
Figure 60. Maturity matrix for drone logistics segments and leading players
Figure 61. Estimated cost per delivery by cost element, van versus drone at low and high density (US$, mid-point estimates)
Figure 62. Disclosed cumulative funding of independent drone delivery and cargo companies (US$ million, estimated, to October 2026)
Figure 63. Taxonomy of autonomous trucking operating models
Figure 64. Hub-to-hub autonomous freight flow
Figure 65. Estimated cumulative capital raised by autonomous freight developers (US$ million, to October 2026)
Figure 66. Milestones in autonomous trucking commercialisation
Figure 67. Per-mile cost of a US Class 8 long-haul truck: human-driven vs Level 4 (US$ per mile)
Figure 68. Early-phase L4 cost per mile vs annual utilisation at three autonomy-fee levels (US$ per mile)
Figure 69. Commercial readiness comparison of autonomous vehicle segments
Figure 70. Technology maturity vs logistics opportunity for autonomous freight segments
Figure 71. Expected autonomous trucking milestones, 2027–2040
Figure 72. Major regulatory milestones for logistics robots, AVs and drones, 2023–2027
Figure 73. EU conformity route for an AMR placed on the market after 20 January 2027
Figure 74. Drone regulation timeline, 2016–2028
Figure 75. Regulatory readiness matrix by country and segment, October 2026 (1 = no pathway, 5 = scalable framework)
Figure 76. Industrial robot installations by country, 2025 (units)
Figure 77. Regional regulatory and policy milestones for logistics autonomy, 2021–2027
Figure 78. Regional maturity heatmap by logistics autonomy segment (2026)
Figure 79. Competitive positioning of leading warehouse automation vendors (Future Markets assessment)
Figure 80. Competitive positioning of outdoor autonomy operators (Future Markets assessment)
Figure 81. Latest annual revenue of leading logistics automation companies (US$ million, converted at approximate 2025 average rates)
Figure 82. Largest disclosed funding rounds in logistics mobile autonomy and adjacent physical AI, 2021–2026 (US$ million)
Figure 83. Selected listings and listing milestones, 2024–2026
Figure 84. Global market revenue, 2025–2040 (US$ billion, base case)
Figure 85. Global market revenue by scenario, 2025–2040 (US$ billion)
Figure 86. Global revenue by application group, 2026–2040 (US$ billion)
Figure 87. Revenue share by application group, 2026 and 2040
Figure 88. Global revenue by category, 2040 (US$ billion, base case)
Figure 89. Revenue mix by category, 2026 vs 2040
Figure 90. Intralogistics transport robots: revenue by category, 2025–2040 (US$ billion)
Figure 91. Intralogistics transport robots: unit sales by category, 2025–2040 (thousand units)
Figure 92. Mobile picking and handling robots: revenue by category, 2025–2040 (US$ billion)
Figure 93. Mobile picking and handling robots: unit sales by category, 2025–2040 (thousand units)
Figure 94. Last-mile delivery robots, vehicles and drones: revenue by category, 2025–2040 (US$ billion)
Figure 95. Last-mile delivery robots, vehicles and drones: unit sales by category, 2025–2040 (thousand units)
Figure 96. Level 4 autonomous trucks and middle-mile freight: revenue by category, 2025–2040 (US$ billion)
Figure 97. Level 4 autonomous trucks and middle-mile freight: unit sales by category, 2025–2040 (thousand units)
Figure 98. Global revenue by region, 2026–2040 (US$ billion)
Figure 99. Regional revenue share, 2026 vs 2040 (%)
Figure 100. Intralogistics and mobile picking robot revenue by end-use industry, 2026 and 2040 (US$ billion)
Figure 101. Announced targets and expected milestones for logistics autonomy, 2027–2040
Figure 102. The emerging autonomous freight chain
Figure 103. Supplier opportunity matrix: maturity versus opportunity (Future Markets assessment)
