Report Content
Chapter 1 Methodology and Scope
1.1 Market scope and definitions
1.2 Base estimates & calculations
1.3 Forecast calculations
1.4 Data Sources
1.4.1 Primary
1.4.2 Data mining sources
1.4.2.1 Paid sources
1.4.2.2 Public sources
Chapter 2 Executive Summary
2.1 Delivery robot industry 3600 synopsis, 2018 - 2032
2.2 Business trends
2.3 Regional trends
2.4 Component trends
2.5 Wheels trends
2.6 End-use trends
Chapter 3 Delivery Robot Industry Insights
3.1 Impact of COVID-19 outbreak
3.1.1 North America
3.1.2 Europe
3.1.3 Asia Pacific
3.1.4 LAMEA
3.2 Impacts of the Russia-Ukraine war
3.3 Delivery robot industry ecosystem analysis
3.3.1 Raw material suppliers
3.3.2 Manufacturers
3.3.3 Software & technology providers
3.3.4 Service providers
3.3.5 Distribution channel analysis
3.3.6 End users
3.3.7 Vendor matrix
3.4 Technology & Innovation landscape
3.4.1 5G and AI in robotics
3.4.2 Impact of IoT and Industry 4.0
3.4.3 Cloud robotics
3.4.4 Internet of Things (IoT)
3.4.5 Machine vision recognition
3.4.6 Robotic arms
3.5 Patent analysis
3.6 Key news & initiatives
3.7 Regulatory landscape
3.7.1 International standards
3.7.1.1 ISO 18646-2:2019: Robotics — Performance criteria and related test methods for service robots
3.7.1.2 ISO 13482
3.7.2 North America
3.7.2.1 Occupational Safety & Health Act (OSHA)
3.7.2.2 STD 01-12-002
3.7.2.3 UL 1740 [57] Robots and Robotic Equipment
3.7.3 Europe
3.7.3.1 RIA 15.06-2013
3.7.3.2 EU product safety framework for advanced robots & autonomous systems
3.7.3.3 Artificial Intelligence Act
3.7.4 Asia Pacific
3.7.4.1 Regulations on the protection of layout designs of integrated circuits
3.7.4.2 Intelligent Robots Development and Distribution Promotion Act: South Korea
3.7.5 South America
3.7.5.1 NR-12
3.7.5.2 Decree Law No. 5452
3.7.6 MEA
3.7.6.1 United Arab Emirates (GCC) Restriction of Hazardous Substances (RoHS) regulation
3.8 Industry impact forces
3.8.1 Growth drivers
3.8.1.1 Increasing use of delivery robots in the retail industry
3.8.1.2 Growth in the hospitality and healthcare industries
3.8.1.3 Increasing use of delivery robots in college campuses
3.8.1.4 Rising e-commerce and online food industries
3.8.1.5 Increasing government initiatives & investments in robot manufacturing companies
3.8.2 Industry pitfalls & challenges
3.8.2.1 High initial investments limiting the entry of new players in the market
3.9 Growth potential analysis
3.10 Porter’s analysis
3.11 PESTEL analysis
Chapter 4 Competitive Landscape, 2022
4.1 Introduction
4.2 Company market share, 2022
4.3 Major Market Players, 2022
4.3.1 JD.com
4.3.2 Alibaba Group (Cainiao Smart Logistics Network Limited)
4.3.3 Kiwibot
4.3.4 Nuro
4.3.5 Relay Robotics
4.3.6 ST Engineering
4.3.7 Starship Technologies
4.4 Competitive positioning matrix
4.5 Strategic outlook matrix
Chapter 5 Delivery Robot Market, By Solution
5.1 Key trends, by solution
5.2 Hardware
5.2.1 Market estimates and forecast, 2018 – 2032
5.3 Software
5.3.1 Market estimates and forecast, 2018 – 2032
Chapter 6 Delivery Robot Market, By End-Use
6.1 Key trends, by end-use
6.2 Food & beverage
6.2.1 Market estimates and forecast, 2018 – 2032
6.3 Retail
6.3.1 Market estimates and forecast, 2018 – 2032
6.4 Healthcare
6.4.1 Market estimates and forecast, 2018 – 2032
6.5 Postal service
6.5.1 Market estimates and forecast, 2018 – 2032
6.6 Others
6.6.1 Market estimates and forecast, 2018 – 2032
Chapter 7 Delivery Robot Market, By Number of Wheels
7.1 Key trends, by number of wheels
7.2 2-wheel robots
7.2.1 Market estimates and forecast, 2018 – 2032
7.3 3-wheel robots
7.3.1 Market estimates and forecast, 2018 – 2032
7.4 4-wheel robots
7.4.1 Market estimates and forecast, 2018 – 2032
7.5 6-wheel robots
7.5.1 Market estimates and forecast, 2018 – 2032
Chapter 8 Delivery Robot Market, By Region
8.1 Key trends, by region
8.2 North America
8.2.1 Market estimates and forecast, 2018 – 2032
8.2.2 Market estimates and forecast, by solution, 2018 – 2032
8.2.3 Market estimates and forecast, by number of wheels, 2018 – 2032
8.2.4 Market estimates and forecast, by end-use, 2018 – 2032
8.2.5 U.S.
8.2.5.1 Market estimates and forecast, 2018 – 2032
8.2.5.2 Market estimates and forecast, by solution, 2018 – 2032
8.2.5.3 Market estimates and forecast, by number of wheels, 2018 – 2032
8.2.5.4 Market estimates and forecast, by end-use, 2018 – 2032
8.2.6 Canada
8.2.6.1 Market estimates and forecast, 2018 – 2032
8.2.6.2 Market estimates and forecast, by solution, 2018 – 2032
8.2.6.3 Market estimates and forecast, by number of wheels, 2018 – 2032
8.2.6.4 Market estimates and forecast, by end-use, 2018 – 2032
8.3 Europe
8.3.1 Market estimates and forecast, 2018 – 2032
8.3.2 Market estimates and forecast, by solution, 2018 – 2032
8.3.3 Market estimates and forecast, by number of wheels, 2018 – 2032
8.3.4 Market estimates and forecast, by end-use, 2018 – 2032
8.3.5 UK
8.3.5.1 Market estimates and forecast, 2018 – 2032
8.3.5.2 Market estimates and forecast, by solution, 2018 – 2032
8.3.5.3 Market estimates and forecast, by number of wheels, 2018 – 2032
8.3.5.4 Market estimates and forecast, by end-use, 2018 – 2032
8.3.6 Germany
8.3.6.1 Market estimates and forecast, 2018 – 2032
8.3.6.2 Market estimates and forecast, by solution, 2018 – 2032
8.3.6.3 Market estimates and forecast, by number of wheels, 2018 – 2032
8.3.6.4 Market estimates and forecast, by end-use, 2018 – 2032
8.3.7 France
8.3.7.1 Market estimates and forecast, 2018 – 2032
8.3.7.2 Market estimates and forecast, by solution, 2018 – 2032
8.3.7.3 Market estimates and forecast, by number of wheels, 2018 – 2032
8.3.7.4 Market estimates and forecast, by end-use, 2018 – 2032
8.3.8 Italy
8.3.8.1 Market estimates and forecast, 2018 – 2032
8.3.8.2 Market estimates and forecast, by solution, 2018 – 2032
8.3.8.3 Market estimates and forecast, by number of wheels, 2018 – 2032
8.3.8.4 Market estimates and forecast, by end-use, 2018 – 2032
8.3.9 Spain
8.3.9.1 Market estimates and forecast, 2018 – 2032
8.3.9.2 Market estimates and forecast, by solution, 2018 – 2032
8.3.9.3 Market estimates and forecast, by number of wheels, 2018 – 2032
8.3.9.4 Market estimates and forecast, by end-use, 2018 – 2032
8.4 Asia Pacific
8.4.1 Market estimates and forecast, 2018 – 2032
8.4.2 Market estimates and forecast, by solution, 2018 – 2032
8.4.3 Market estimates and forecast, by number of wheels, 2018 – 2032
8.4.4 Market estimates and forecast, by end-use, 2018 – 2032
8.4.5 China
8.4.5.1 Market estimates and forecast, 2018 – 2032
8.4.5.2 Market estimates and forecast, by solution, 2018 – 2032
8.4.5.3 Market estimates and forecast, by number of wheels, 2018 – 2032
8.4.5.4 Market estimates and forecast, by end-use, 2018 – 2032
8.4.6 India
8.4.6.1 Market estimates and forecast, 2018 – 2032
8.4.6.2 Market estimates and forecast, by solution, 2018 – 2032
8.4.6.3 Market estimates and forecast, by number of wheels, 2018 – 2032
8.4.6.4 Market estimates and forecast, by end-use, 2018 – 2032
8.4.7 Japan
8.4.7.1 Market estimates and forecast, 2018 – 2032
8.4.7.2 Market estimates and forecast, by solution, 2018 – 2032
8.4.7.3 Market estimates and forecast, by number of wheels, 2018 – 2032
8.4.7.4 Market estimates and forecast, by end-use, 2018 – 2032
8.4.8 South Korea
8.4.8.1 Market estimates and forecast, 2018 – 2032
8.4.8.2 Market estimates and forecast, by solution, 2018 – 2032
8.4.8.3 Market estimates and forecast, by number of wheels, 2018 – 2032
8.4.8.4 Market estimates and forecast, by end-use, 2018 – 2032
8.4.9 Taiwan
8.4.9.1 Market estimates and forecast, 2018 – 2032
8.4.9.2 Market estimates and forecast, by solution, 2018 – 2032
8.4.9.3 Market estimates and forecast, by number of wheels, 2018 – 2032
8.4.9.4 Market estimates and forecast, by end-use, 2018 – 2032
8.5 LAMEA
8.5.1 Market estimates and forecast, 2018 – 2032
8.5.2 Market estimates and forecast, by solution, 2018 – 2032
8.5.3 Market estimates and forecast, by number of wheels, 2018 – 2032
8.5.4 Market estimates and forecast, by end-use, 2018 – 2032
8.5.5 Brazil
8.5.5.1 Market estimates and forecast, 2018 – 2032
8.5.5.2 Market estimates and forecast, by solution, 2018 – 2032
8.5.5.3 Market estimates and forecast, by number of wheels, 2018 – 2032
8.5.5.4 Market estimates and forecast, by end-use, 2018 – 2032
8.5.6 Mexico
8.5.6.1 Market estimates and forecast, 2018 – 2032
8.5.6.2 Market estimates and forecast, by solution, 2018 – 2032
8.5.6.3 Market estimates and forecast, by number of wheels, 2018 – 2032
8.5.6.4 Market estimates and forecast, by end-use, 2018 – 2032
8.5.7 GCC
8.5.7.1 Market estimates and forecast, 2018 – 2032
8.5.7.2 Market estimates and forecast, by solution, 2018 – 2032
8.5.7.3 Market estimates and forecast, by number of wheels, 2018 – 2032
8.5.7.4 Market estimates and forecast, by end-use, 2018 – 2032
8.5.8 South Africa
8.5.8.1 Market estimates and forecast, 2018 – 2032
8.5.8.2 Market estimates and forecast, by solution, 2018 – 2032
8.5.8.3 Market estimates and forecast, by number of wheels, 2018 – 2032
8.5.8.4 Market estimates and forecast, by end-use, 2018 – 2032
Chapter 9 Company Profiles
9.1 Alibaba Group
9.1.1 Business Overview
9.1.2 Financial Data
9.1.3 Product Landscape
9.1.4 Strategic Outlook
9.1.5 SWOT Analysis
9.2 Alpha Asimov
9.2.1 Business Overview
9.2.2 Financial Data
9.2.3 Product Landscape
9.2.4 SWOT Analysis
9.3 Boston Dynamics
9.3.1 Business Overview
9.3.2 Financial Data
9.3.3 Product Landscape
9.3.4 Strategic Outlook
9.3.5 SWOT Analysis
9.4 Eliport
9.4.1 Business Overview
9.4.2 Financial Data
9.4.3 Product Landscape
9.4.4 SWOT Analysis
9.5 JD.com (Jingdong)
9.5.1 Business Overview
9.5.2 Financial Data
9.5.3 Product Landscape
9.5.4 Strategic Outlook
9.5.5 SWOT Analysis
9.6 Kiwibot
9.6.1 Business Overview
9.6.2 Financial Data
9.6.3 Product Landscape
9.6.4 Strategic Outlook
9.6.5 SWOT Analysis
9.7 Nuro
9.7.1 Business Overview
9.7.2 Financial Data
9.7.3 Product Landscape
9.7.4 Strategic Outlook
9.7.5 SWOT Analysis
9.8 Ottonomy
9.8.1 Business Overview
9.8.2 Financial Data
9.8.3 Product Landscape
9.8.4 Strategic Outlook
9.8.5 SWOT Analysis
9.9 Panasonic Corporation
9.9.1 Business Overview
9.9.2 Financial Data
9.9.3 Product Landscape
9.9.4 Market Strategy
9.9.5 SWOT Analysis
9.10 Piaggio & C. SpA
9.10.1 Business Overview
9.10.2 Financial Data
9.10.3 Product Landscape
9.10.4 Market Strategy
9.10.5 SWOT Analysis
9.11 Relay Robotics
9.11.1 Business Overview
9.11.2 Financial Data
9.11.3 Product Landscape
9.11.4 Strategic Outlook
9.11.5 SWOT Analysis
9.12 Richtech Robotics
9.12.1 Business Overview
9.12.2 Financial Data
9.12.3 Product Landscape
9.12.4 SWOT Analysis
9.13 Starship Technologies
9.13.1 Business Overview
9.13.2 Financial Data
9.13.3 Product Landscape
9.13.4 Strategic Outlook
9.13.5 SWOT Analysis
9.14 ST Engineering
9.14.1 Business Overview
9.14.2 Financial Data
9.14.3 Product Landscape
9.14.4 Strategic Outlook
9.14.5 SWOT Analysis
9.15 Suzhou Pangolin Robot Corp (CSJBot)
9.15.1 Business Overview
9.15.2 Financial Data
9.15.3 Product Landscape
9.15.4 Strategic Outlook
9.15.5 SWOT Analysis
