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Global Educational Robot Market to reach USD 3.18 billion by 2028.

Global Educational Robot Market Size study, by Type (Service Robots, Industrial Robots), by Component (Hardware, Software), by Educational Level (Elementary & High School Education, Higher Education, Special Education) and Regional Forecasts 2022-2028

Product Code: ENGE-30859690
Publish Date: 17-05-2022
Page: 200

Global Educational Robot Market is valued at approximately USD 1.12 billion in 2021 and is anticipated to grow with a healthy growth rate of more than 16.10% over the forecast period 2022-2028. Educational Robots or Educational Robotic Technology is a subfield of Robotics and Information Engineering. An Educational Robot is a locomotive device capable of moving around, often without guidance and support. Hardware components such as sensors, control systems and other mechanical components are used to regulate these robots. Gradual increase in use of Robots in manufacturing areas to create new job prospects, rise in demand for collaborative Robots in industrial & academic sectors and increase in Humanoid robot research and development, has driven the adoption of Educational Robot across the projected period. For Instance: C-Learn is a machine learning technique created by MIT’s Computer Science and Artificial Intelligence Laboratory. Non-coders may teach robots motions and tasks using C-Learn by first supplying some basic information about the objects to be manipulated, then showing the robot a single demonstration on how to complete the task. Also, deployment of Educational Robots in High School and deployment of Humanoid Robots for students with special needs are most likely to boost the overall growth of the Educational Robot Market. However, high cost of Educational Robots can obstruct the market’s expansion over the projection period of 2022-2028.
The key regions considered for the global Educational Robot Market study include Asia Pacific, North America, Europe, Latin America and Rest of the World. North America is the leading region across the world. Advancements in robotic technologies and research are driving market growth in North America. Whereas, Asia Pacific is also anticipated to exhibit the highest growth rate over the forecast period 2022-2028. The market is expected to grow during the projected period due to growing advancements in education system and government funding programs.

Major market players included in this report are:
Abb
Fanuc
Yaskawa
Kuka
Universal robots
Softbank robotics group
Hanson robotics
Robotis
Robolink
Probotics america

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming eight years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within each of the regions and countries involved in the study. Furthermore, the report also caters the detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, the report shall also incorporate available opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:
By Type:
Service Robots
Industrial Robots
By Component:
Hardware
Software
By Educational Level:
Elementary & High School Education
Higher Education
Special Education
By Region:
North America
U.S.
Canada
Europe
UK
Germany
France
Spain
Italy
ROE

Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC
Latin America
Brazil
Mexico
Rest of the World

Furthermore, years considered for the study are as follows:

Historical year – 2018, 2019, 2020
Base year – 2021
Forecast period – 2022 to 2028

Target Audience of the Global Educational Robot Market in Market Study:

Key Consulting Companies & Advisors
Large, medium-sized, and small enterprises
Venture capitalists
Value-Added Resellers (VARs)
Third-party knowledge providers
Investment bankers
Investors

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2020-2028 (USD Billion)
1.2.1. Educational Robot Market, by Region, 2020-2028 (USD Billion)
1.2.2. Educational Robot Market, by Type, 2020-2028 (USD Billion)
1.2.3. Educational Robot Market, by Component, 2020-2028 (USD Billion)
1.2.4. Educational Robot Market, by Educational Level, 2020-2028 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Educational Robot Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Scope of the Study
2.2.2. Industry Evolution
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Educational Robot Market Dynamics
3.1. Educational Robot Market Impact Analysis (2020-2028)
3.1.1. Market Drivers
3.1.1.1. Gradual Increase in the use of Robots in manufacturing areas to create new job prospects
3.1.1.2. Rise in demand for Collaborative Robots in Industrial and Academic sectors
3.1.1.3. Increase in Humanoid robot research and development
3.1.2. Market Challenges
3.1.2.1. High Cost of Educational Robots
3.1.3. Market Opportunities
3.1.3.1. Deployment of Educational Robots in High School
3.1.3.2. Deployment of Humanoid Robots for Students with special needs

Chapter 4. Global Educational Robot Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.1.6. Futuristic Approach to Porter’s 5 Force Model (2018-2028)
4.2. PEST Analysis
4.2.1. Political
4.2.2. Economical
4.2.3. Social
4.2.4. Technological
4.3. Investment Adoption Model
4.4. Analyst Recommendation & Conclusion
4.5. Top investment opportunity
4.6. Top winning strategies
Chapter 5. Risk Assessment: COVID-19 Impact
5.1.1. Assessment of the overall impact of COVID-19 on the industry
5.1.2. Pre COVID-19 and post COVID-19 market scenario
Chapter 6. Global Educational Robot Market, by Type
6.1. Market Snapshot
6.2. Global Educational Robot Market by Type, Performance – Potential Analysis
6.3. Global Educational Robot Market Estimates & Forecasts by Type, 2018-2028 (USD Billion)
6.4. Educational Robot Market, Sub Segment Analysis
6.4.1 Service Robots
6.4.2 Industrial Robots

Chapter 7. Global Educational Robot Market, by Component
7.1. Market Snapshot
7.2. Global Educational Robot Market by Component, Performance – Potential Analysis
7.3. Global Educational Robot Market Estimates & Forecasts by Component, 2018-2028 (USD Billion)
7.4. Educational Robot Market, Sub Segment Analysis
7.4.1 Hardware
7.4.2 Software

Chapter 8. Global Educational Robot Market, by Educational Level
8.1. Market Snapshot
8.2. Global Educational Robot Market by Educational Level, Performance – Potential Analysis
8.3. Global Educational Robot Market Estimates & Forecasts by Educational Level, 2018-2028 (USD Billion)
8.4. Educational Robot Market, Sub Segment Analysis
8.4.1 Elementary and High School Education
8.4.2 Higher Education
8.4.3 Special Education

Chapter 9. Global Educational Robot Market, Regional Analysis

9.1. Educational Robot Market, Regional Market Snapshot
9.2. North America Educational Robot Market
9.2.1. U.S. Educational Robot Market
9.2.1.1. Type breakdown estimates & forecasts, 2018-2028
9.2.1.2. Component breakdown estimates & forecasts, 2018-2028
9.2.1.3. Educational Level breakdown estimates & forecasts, 2018-2028
9.2.2. Canada Educational Robot Market
9.3. Europe Educational Robot Market Snapshot
9.3.1. U.K. Educational Robot Market
9.3.2. Germany Educational Robot Market
9.3.3. France Educational Robot Market
9.3.4. Spain Educational Robot Market
9.3.5. Italy Educational Robot Market
9.3.6. Rest of Europe Educational Robot Market
9.4. Asia-Pacific Educational Robot Market Snapshot
9.4.1. China Educational Robot Market
9.4.2. India Educational Robot Market
9.4.3. Japan Educational Robot Market
9.4.4. Australia Educational Robot Market
9.4.5. South Korea Educational Robot Market
9.4.6. Rest of Asia Pacific Educational Robot Market
9.5. Latin America Educational Robot Market Snapshot
9.5.1. Brazil Educational Robot Market
9.5.2. Mexico Educational Robot Market
9.6. Rest of The World Educational Robot Market

Chapter 10. Competitive Intelligence
10.1. Top Market Strategies
10.2. Company Profiles
10.2.1 ABB
10.2.1.1 Key Information
10.2.1.2 Overview
10.2.1.3 Financial (Subject to Data Availability)
10.2.1.4 Product Summary
10.2.1.5 Recent Developments

10.2.2 FANUC
10.2.3 YASKAWA
10.2.4 KUKA
10.2.5 UNIVERSAL ROBOTS
10.2.6 SOFTBANK ROBOTICS GROUP
10.2.7 HANSON ROBOTICS
10.2.8 ROBOTIS
10.2.9 ROBOLINK
10.2.10 PROBOTICS AMERICA

Chapter 11. Research Process
11.1 Research Process
11.1.1 Data Mining
11.1.2 Analysis
11.1.3 Market Estimation
11.1.4 Validation
11.1.5 Publishing
11.2 Research Attributes
11.3 Research Assumption

At Bizwit Research and Consultancy, we employ a thorough and iterative research methodology with the goal of minimizing discrepancies, ensuring the provision of highly accurate estimates and predictions over the forecast period. Our approach involves a combination of bottom-up and top-down strategies to effectively segment and estimate quantitative aspects of the market, utilizing our proprietary data & AI tools. Our Proprietary Tools allow us for the creation of customized models specific to the research objectives. This enables us to develop tailored statistical models and forecasting algorithms to estimate market trends, future growth, or consumer behavior. The customization enhances the accuracy and relevance of the research findings.
We are dedicated to clearly communicating the purpose and objectives of each research project in the final deliverables. Our process begins by identifying the specific problem or challenge our client wishes to address, and from there, we establish precise research questions that need to be answered. To gain a comprehensive understanding of the subject matter and identify the most relevant trends and best practices, we conduct an extensive review of existing literature, industry reports, case studies, and pertinent academic research.
Critical elements of methodology employed for all our studies include:
Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
In addition to primary sources, we extensively utilize secondary sources to enhance our research. These include directories, databases, journals focusing on related industries, company newsletters, and information portals such as Bloomberg, D&B Hoovers, and Factiva. These secondary sources enable us to identify and gather valuable information for our comprehensive, technical, market-oriented, and commercial study of the market. Additionally, we utilize AI algorithms to automate the collection of vast amounts of data from various sources such as surveys, social media platforms, online transactions, and web scraping. And employ Big Data technologies for storage and processing of large datasets, ensuring that no valuable information is missed during the data collection process.
Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
Insight Generation & Report Presentation:
After conducting the research, our experts analyze the findings in relation to the research objectives and the specific needs of the client. They generate valuable insights and recommendations that directly address the client’s business challenges. These insights are carefully connected to the research findings to provide a comprehensive understanding.
Next, we create a well-structured research report that effectively communicates the research findings, insights, and recommendations to the client. To enhance clarity and comprehension, we utilize visual aids such as charts, graphs, and tables. These visual elements are employed to present the data in an engaging and easily understandable format, ensuring that the information is accessible and visually appealing to the client. Our aim is to deliver a clear and concise report that conveys the research findings effectively and provides actionable recommendations to meet the client’s specific needs.

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