Delivery Robot Market - By Solution (Hardware, Software), By Number of wheels (2-wheel robots, 3-wheel robots, 4-wheel robots, 6-wheel robots), By End-Use (Food & Beverage, Retail, Healthcare, Postal Service) & Forecast, 2023

Description

List of Tables

Global Delivery Robot Market size is anticipated to expand significantly through 2032, owing to the growing use of delivery robots across college campuses. Many universities across the U.S. are increasingly using delivery robots to test their efficacy on college premises. In fact, the Ohio State University is one such institution that partnered with Cartken, a sidewalk delivery robot firm to test 50 fully automated delivery robots.

Citing another instance, in December 2022, Kiwibot, a last-mile delivery robot firm, inked a deal with Grubhub, a prominent food ordering marketplace, for the next-gen robot delivery in college premises. Escalating product innovations in the field are further positively influencing the industry landscape. For instance, in August 2022, Ottonomy, a prominent autonomous delivery robot manufacturer, announced the launch of the Ottobot 2.0, a second-generation delivery robot.

The overall delivery robot market is segmented based on component, number of wheels, end-use, and region.

Based on components, the delivery robot market size from the software segment is anticipated to attain sizeable gains through 2032. Increasing efforts by key robot manufacturers towards developing delivery robots with superior functionalities have increased the demand for software components. Moreover, many industry players, such as Starship Technologies, are also investing in testing programs for self-driving delivery robots, which is expected to boost segment growth.

3-wheel delivery robot industry size is slated to be worth over USD 500 million by 2032. High durability of these robots has increased their adoption for long-term use. These robots can move quickly in any direction, which helps optimize the delivery process. Additionally, they are highly efficient than their 2-wheel counterparts. The growing focus of key industry participants on launching state-of-the-art 3-wheel delivery robots will further positively contribute to segment expansion.

In terms of end-use, delivery robot market share from the retail segment is poised to grow considerably through 2032, owing to the growing focus of retail chains on enhancing last-mile delivery systems. Many retail giants such as Target and Walmart are investing in delivery robots to optimize their workflow efficiency. Delivery robots ensure a predictable delivery, which highly complements the retail space. They also allow faster last-mile delivery and enhance the productivity of retail stores by eliminating the manual errors associated with delivery.

On the regional front, Asia Pacific delivery robot industry value is expected to reach over USD 3 billion by 2032. Strong presence of industry players, such as the Alibaba Group, investing in product innovations, will contribute to the growth of the regional industry. Moreover, rapid urbanization in emerging economies such as China and Japan has increased the demand for delivery robots to cater to the growing demand in the e-commerce space.

Product Code: 5558

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 360 degree 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