This report delves into the global market development of Embodied Intelligence Robots, exploring technological advancements and future trends. It focuses on analyzing the technical features and application scenarios of categories such as humanoid robots, digital robots, and mobile robots (AMR/AGV). By combining market data and industry case studies, the report evaluates the commercialization status and future growth potential of these technologies. Additionally, it covers the competitive landscape of key market players, discusses technical bottlenecks, policy environments, and investment opportunities, providing valuable decision-making insights for enterprises and investors.
1. Basic Analysis of Embodied Intelligence Robots
1.1 Definition and Explanation of Embodied Intelligence
Embodied Intelligence refers to the capability of robots or AI systems to possess the ability to perceive, cognize, decide, and move autonomously, much like living organisms, while interacting with their environment. This concept breaks through the traditional limitations of AI, which relies solely on data analysis, enabling robots to "understand the world" and "act on the world," facilitating higher-level intelligent applications.
Compared to traditional Artificial Intelligence (AI), embodied intelligence not only relies on algorithms such as deep learning and reinforcement learning for data processing but also integrates physical motion control capabilities, allowing robots to perform autonomous tasks in complex physical environments. For example, while traditional AI is mainly used for data analysis and decision support, embodied intelligence robots can navigate autonomously, perceive their environment, and interact in real-time. This makes them applicable in a wide range of fields, such as industrial manufacturing, logistics, healthcare, and services.
The core features of embodied intelligence include:
Perception: Robots collect environmental information through multimodal sensors (such as cameras, LiDAR, ultrasonic sensors, and tactile sensors) to achieve precise environmental perception.
Decision-Making: Using AI algorithms like deep learning and reinforcement learning, robots can analyze perceived information and devise appropriate behavioral strategies.
Motion: Robots rely on intelligent chassis or biomimetic structures to achieve autonomous movement, obstacle avoidance, path planning, and complete designated tasks.
According to a report by Grand View Research, the global computer vision market is estimated to reach $19.82 billion in 2024 and is expected to grow at a compound annual growth rate (CAGR) of 19.8% from 2025 to 2030, providing technological support for the environmental perception capabilities of embodied intelligent robots. Additionally, Statista (2024) forecasts that the voice recognition market will reach $8.58 billion by 2025 and grow at a CAGR of 13.09%, reaching $15.87 billion by 2030. This will further drive the application of embodied intelligent robots in human-machine interaction.
Embodied intelligent robots can be classified into the following categories based on their functions and forms:
Humanoid Robots: Such as Tesla Optimus and Agility Robotics' Digit, these robots mimic human form and possess complex motion capabilities, applicable in smart manufacturing, domestic services, and more.
Digital Robots: Combining digital human technology, like Reeman Digital Human Robot, which integrates AI voice, computer vision, and autonomous mobility, applicable in enterprise front desks, mall guidance, and other scenarios.
Mobile Robots (AMR/AGV): Like Amazon's Kiva robot, warehouse logistics AGVs, and autonomous delivery robots, widely used in smart manufacturing and logistics industries.
Biomorphic Robots: Mimicking the movement of animals or natural organisms, such as Boston Dynamics' Spot robot, used for inspection, search and rescue, and other specialized tasks.
1.2 Key Technology: Intelligent Perception
Intelligent perception is one of the core capabilities of embodied intelligent robots, enabling them to perceive the environment in real-time, identify targets, and act autonomously in complex scenarios. Currently, intelligent perception mainly relies on the following key technologies:
Computer Vision (3D SLAM, Object Recognition)
Computer vision technology helps robots perceive the environment in real-time and recognize objects. Among them, 3D SLAM (Simultaneous Localization and Mapping) technology allows robots to build maps in unknown environments and achieve autonomous navigation. Object recognition technology enables robots to accurately identify objects and people, improving interaction capabilities.
Voice Recognition and Natural Language Processing (NLP)
Embodied intelligent robots typically integrate AI voice technology, enabling smooth voice interaction and enhancing autonomous service capabilities. Natural language processing (NLP) optimizes the robot's ability to understand human language. For example, the Reeman Digital Human Robot can provide services such as corporate information queries and weather reports, enhancing the naturalness of human-machine interaction.
Multimodal Fusion Sensing (LiDAR, Ultrasonic, IMU, Infrared Sensors)
Robots can enhance their environmental perception abilities by integrating LiDAR (Light Detection and Ranging), ultrasonic sensors, Inertial Measurement Units (IMUs), and infrared sensors, thereby improving autonomous obstacle avoidance and path planning accuracy.
1.3 Key Technology: Motion Control
Motion control technology determines the autonomous action capabilities of embodied intelligent robots, involving the following aspects:
Robot Chassis (Wheeled, Tracked, Bipedal, Humanoid Biomimetic)
Wheeled/Tracked Chassis: Such as AMR and AGV robots, widely used in logistics, warehousing, and other scenarios.
Bipedal Humanoid Robots: Such as Tesla Optimus, which can adapt to complex terrains and improve flexibility.
Motion Planning (Path Optimization, Obstacle Avoidance, Autonomous Decision-Making)
AI algorithms optimize the motion path, enhancing the robot's ability to make autonomous decisions in complex environments, enabling dynamic path planning and obstacle avoidance.
Reinforcement Learning and Adaptive Control
By employing deep reinforcement learning, robots can continuously optimize their movement strategies, enhancing stability and precision.
1.4 Key Technology: Environmental Interaction
Environmental interaction capability determines how robots interact naturally and effectively with humans and their surroundings. This includes the following core technologies:
Human-Machine Interaction (Voice, Gesture, Facial Expression Recognition)
For example, the Reeman Digital Robot combines AI voice technology and 3D digital human models to provide intelligent front desk services and human-like communication with users.
Cloud Collaboration and Edge Computing
Robots, integrated with 5G and AI cloud computing, can enhance data processing capabilities, enabling remote control and real-time optimization.
Swarm Intelligence (Multi-Robot Cooperation, Distributed Control)
In industrial applications, multiple AMR robots can collaborate and optimize production and logistics processes.
2. Market Status and Competitive Landscape
2.1 Global Market Size and Growth
Overall Market:
By 2024, the global embodied intelligent AI market is projected to reach $2.5335 billion and is expected to grow to $8.7565 billion by 2033, with a compound annual growth rate (CAGR) of 15.0%.
2.2 Regional Market Analysis
North America:
North America is expected to have the fastest-growing AI market within the robotics sector during the forecast period. The growing demand for personalized and on-demand services is driving the adoption of AI-driven robotics technology in the service industry. With the rise of e-commerce, food delivery, and ride-sharing platforms, robots are required to provide efficient and reliable customer service in real-time. The U.S. leads the AI robotics market, driven by a strong industrial base and a focus on automation and efficiency, which is promoting the adoption of AI robotic technology across various sectors, including manufacturing, healthcare, logistics, agriculture, and defense.
Asia-Pacific (APAC):
The Asia-Pacific region dominated the global robotics AI market with a 44.6% share in 2023. Regulatory requirements and safety concerns are driving the adoption of AR (Augmented Reality) technology. As safety regulations become more stringent, automotive manufacturers are shifting towards AR-based driver assistance systems to enhance situational awareness and reduce driver distraction.
In the Asia-Pacific region, China accounts for 19.4% of the AI robotics market revenue. The rapid urbanization and infrastructure development in China are driving the application of AI robotics in construction, logistics, and smart city initiatives. AI robots are deployed in construction projects to improve efficiency, safety, and accuracy, reduce construction time and costs, while enhancing quality and sustainability. In smart city plans, AI-supported robots are used for security monitoring, public transportation management, and environmental monitoring, helping to create more efficient, sustainable, and livable urban environments.
India's AI robotics market is expected to grow at the fastest CAGR during the forecast period. The Indian government is focusing on digital transformation and innovation through initiatives like the National AI Strategy and Digital India Program, which is driving market growth. These initiatives aim to leverage AI and robotics technology to address societal challenges, foster economic growth, and improve citizens' quality of life. The government's support for AI research, development, and adoption has created a favorable environment for market growth, promoting collaboration among industries, academia, and government agencies to accelerate innovation and technology adoption.
Europe:
Europe holds a significant position in the global robotics market, particularly in the industrial robotics sector. According to data from Fortune Business Insights, Europe is the second-largest regional market for industrial robots globally, with an expected CAGR of 14.1% during the forecast period.
In Europe, Germany is the largest robotics market. In 2022, approximately 26,000 robots were installed in Germany, a 3% year-on-year growth, accounting for 37% of the EU's total installations. Italy ranks second with nearly 12,000 robots installed in 2022, showing a 10% year-on-year growth, marking a historical high, and accounting for 16% of the EU's total installations. France ranked third, with a total of 7,400 installations in 2022, growing by 15%. Spain and Poland also showed strong growth in robot installations, with a 12% and 9% increase, respectively, over the last 9 years.
In terms of industry applications, the automotive manufacturing sector is the largest application for industrial robots in the EU, accounting for 38.7%. The European service robot market is also growing rapidly. According to a report by Mordor Intelligence, the European service robot market is expected to grow at a CAGR of approximately 14% from 2021 to 2026. The application of service robots in fields like fieldwork, logistics, and construction is expanding, particularly in specialized cleaning and military applications. Germany, as Europe's largest robotics market, leads not only in industrial robots but also in the service robot sector.
2.3 Key Players and Competitive Strategies
Tech Giants' Involvement:
Global tech giants are entering the embodied intelligence sector, driving industrial development. Nvidia founder Jensen Huang emphasized at the 2025 Consumer Electronics Show (CES) that "the next frontier of AI is embodied AI" and predicted that the "ChatGPT moment" for general-purpose humanoid robots is coming soon. Tesla is aiming to produce over 10,000 humanoid robots by 2025 to lead the industry. OpenAI is also actively investing and collaborating in the embodied intelligence field.
Robotics Companies:
Several robotics companies have made significant advancements in embodied intelligence. Humanoid robots such as Boston Dynamics' Atlas, Agility Robotics' Digit, and UBTECH's Walker X are continuously breaking through in technology and application. Chinese companies like Estun, Ecovacs, Tianzhihang, and Reeman are also actively investing in the research and development of embodied intelligent robots.
Competitive Strategies:
Technological Collaboration: Companies are strengthening technological collaborations to advance the development of embodied intelligence. For example, OpenAI and Figure AI jointly developed the humanoid robot NEO, combining both parties' resources to accelerate product development.
Vertical Integration: Some companies are adopting a vertical integration strategy to optimize cost structures and improve product competitiveness. Tesla, for example, develops its own AI chips to optimize the cost and performance of the Optimus robot, enhancing its market competitiveness.
2.4 Segment Analysis
Humanoid Robot Features and Applications
Technical Features: High degree of freedom in mechanical structure, biomimetic motion control, complex environmental adaptation
Typical Products: Tesla Optimus, Boston Dynamics Atlas, Agility Robotics Digit, Unitree H1
Main Application Scenarios: Industrial manufacturing, home services, medical care, human-robot interaction
Market Outlook: According to GGII (Gaogong Robot Industry Research Institute), the global humanoid robot market is expected to exceed $20 billion by 2030, with China's market expected to reach $5 billion (based on China accounting for 25% of the global service robot market).
Digital Human Robot Features and Applications
Technical Features: Smart robot chassis + display screen (digital human) combined with AI, natural language processing (NLP), and multimodal interaction technology, capable of simulating real humans for voice, text, and visual interaction.
Main Application Scenarios:
Enterprise Reception: Welcoming visitors in company lobbies and providing company introductions, meeting room directions, etc.
Mall and Exhibition Hall Navigation: Acting as intelligent guides to recommend products and display brand information.
Government/Bank/Hotel Services: Providing policy consultation, business guidance, and explaining self-service processes.
Medical Institution Information Services: Helping patients with registration queries, department locations, and hospital navigation.
The combination of digital humans and robots has automated over 50% of positions in enterprise front desks, navigation, and customer service. It is expected that more than 80% of large malls and corporate front desks will adopt intelligent digital robots in the next five years.
China's Market Demand for Digital Humans + Robots is growing rapidly, particularly in government, banking, healthcare, and commercial industries. The shipment volume of digital human robots in China is expected to grow by 35% annually from 2025 to 2030.
Case Study: Deployment of Reeman Digital Human Robot at the Reception
A technology company has deployed a Reeman digital human robot at its reception. The robot automatically greets visitors and engages in conversation via AI voice and the digital human on the display screen.
Process:
Visitor Entry → The robot proactively greets the visitor and asks the purpose of the visit.
Navigation Guidance → The robot autonomously guides the visitor to the meeting room or office area.
Company Introduction → The robot can display the company's history, products, and other information through voice and video.
Weather/News/Business Inquiries → Visitors can ask for real-time weather updates, news, and business-related information, and the robot provides responses.
Results:
Visitor Wait Time Reduced by 40%: The time spent waiting for assistance was significantly decreased.
Front Desk Efficiency Improved by 60%: The robot helped streamline the check-in process and other front desk tasks.
Visitor Satisfaction Increased by 30%: Enhanced AI interaction resulted in a better experience for visitors.
Company Brand Image Enhanced: The use of advanced technology and innovation boosted the company's brand image and showcased its cutting-edge capabilities.
Mobile Robot Features and Applications (AMR/AGV)
Technical Features: Autonomous navigation (SLAM), intelligent obstacle avoidance, task scheduling
Typical Products: Reeman handling robots, MiR (Mobile Industrial Robots), Hikvision AMR
Main Application Scenarios: Smart logistics, unmanned warehousing, medical delivery
Market Outlook: According to Research and Markets, the AMR market size was $6 billion in 2023 and is expected to grow to $26 billion by 2030.
3. Embodied Intelligence Robot Industry Trends
3.1 Deep Integration of AI and Embodied Intelligence
The deep integration of embodied intelligence and AI is driving robots from "program execution" to "autonomous decision-making," with large models, edge computing, and cloud collaboration becoming key driving forces.
Large Models Empower Decision Optimization
Generative AI and Large Language Models (LLM): Large models like GPT-4 and DeepSeek significantly enhance robots' ability to understand natural language commands. For example, Google's RT-X platform uses LLMs to enable robotic arms to break down complex tasks (e.g., "tidy up a room") and autonomously perform steps. This has been applied in tasks such as folding clothes and precision assembly.
End-to-End Models and Hierarchical Decision-Making: End-to-end models, such as Google RT-2, directly map perception to actions, while hierarchical models (like OpenAI's Figure 01) reduce computational requirements by modularizing tasks, accelerating the generalization of complex tasks.
Cloud Collaboration and Edge Computing
5G and edge computing technologies support real-time data processing. Warehouse robots, through localized AI models, respond to dynamic logistics demands, improving efficiency by 40%.
The "GenieOperator-1" model from Zhiyuan Robotics integrates multimodal large models with hybrid expert systems, supporting small-sample generalization and cross-entity applications, significantly enhancing environmental perception efficiency.
3.2 Industry Penetration Progress
Automation and manufacturing are the leading application areas in the embodied intelligence AI market, with a projected market share of 27.1% by the end of 2024. These sectors rely heavily on efficiency, productivity, and cost-effectiveness. Autonomous robots and intelligent machines are revolutionary solutions that simplify tasks, minimize human error, and improve manufacturing precision. Embodied intelligence robots are rapidly penetrating core industries like manufacturing, healthcare, and retail, driving industrial digital transformation. Various sectors are embracing these technologies to reduce operating costs while increasing output, making them critical drivers in the competitive market.
Manufacturing:
Smart Factories and Collaborative Robots: AMR (Autonomous Mobile Robots) automate material handling in car manufacturing. Tesla's Optimus humanoid robot is planned for mass production in 2025, aiming to replace repetitive assembly tasks.
Demand for Flexible Production: Research in Chongqing indicates that the demand for embodied intelligence robots in the automotive and equipment manufacturing industries is focused on precision assembly and quality inspection. By 2027, industrial robot penetration is expected to reach 35%.
Healthcare:
Surgical and Rehabilitation Robots: In 2023, China's medical robotics market reached 10.8 billion yuan. The Da Vinci surgical robot has completed over one million minimally invasive surgeries with an accuracy of 0.1mm. Rehabilitation robots (e.g., Rewalk exoskeleton) help paralyzed patients regain walking ability.
Aging Population Drives Care Robot Demand: With policy support, the development of elderly care robots is accelerating. For example, community service robots can provide daily care and health monitoring.
Retail:
Smart Shopping and Unmanned Delivery: The Pepper robot enhances shopping efficiency in Japanese malls through emotion recognition and voice interaction, improving customer satisfaction by 25%. Logistics robots (e.g., Geek+ AMR) reduce costs in warehouse sorting by 40%.
Offline Retail Intelligence: Digital human robots (e.g., Reeman digital human robot) integrate 3D digital human technology for automated brand display and customer inquiries in malls. The global digital human market is expected to exceed $150 billion by 2028.
3.3 Technological Breakthroughs and Market Outlook
Technological Bottlenecks and Breakthrough Directions
Perception and Energy Consumption Challenges: Issues like environmental complexities (e.g., rain or snow disrupting lidar) and the limited battery life of Tesla's Optimus (only 4 hours) remain unresolved. Biomimetic materials (e.g., Harvard's Octobot flexible sensors) and brain-inspired computing are expected to drive performance improvements.
Data Bottleneck: Generalizing single skills requires millions of data points for training. The National Innovation Center's virtual-real simulation platform, producing 10TB of data daily, is accelerating data standardization and open sharing.
Policy and Capital Drivers
China's Government Work Report has officially included "embodied intelligence" in its future industrial plan. The market is expected to reach $90 billion by 2030, with a compound annual growth rate (CAGR) exceeding expectations.
Local policies in places like Beijing and Shanghai focus on technological R&D and scenario openness. The National Innovation Center has established the first universal dataset standard (RoboMIND) to promote industry standardization.
Future Trends for the Next Decade
Software and Hardware Co-Evolution: With rapid advancements in algorithms and training platforms, hardware (e.g., high-precision sensors) remains limited by material processes. Companies need to prioritize building software ecosystems (e.g., simulation platforms).
Ethics and Security: If embodied intelligent agents evolve beyond predefined boundaries, algorithms for behavioral constraints and human-machine rights and responsibilities must be established to prevent technological loss of control.
Technological Progress in AI and Robotics
The continuous advancement in AI and robotics technology is driven by research progress in fields like machine learning and deep learning, which contribute to the development of more advanced autonomous robots. The growth of the machine learning market further fuels innovation in these areas. While applications of AI-driven robots in industrial automation, data collection, and autonomous navigation are already operational, these technologies are executed with higher precision and speed. These advancements in technology, combined with improvements in robotic hardware and AI processing capabilities, will undoubtedly propel the growth of the embodied intelligence market as more industries leverage AI systems to reduce operational costs.
With multimodal perception, deep AI integration, and vertical scenario penetration, embodied intelligence robots are moving from laboratories to large-scale commercial applications, becoming the core engine of Industry 4.0 and intelligent societies.
4. Future Outlook of Embodied AI Robots
4.1 Potential Development Opportunities
Commercialization Breakthrough: Humanoid Robots + AI for Repetitive Labor Replacement
Humanoid robots combined with AI technology can mimic human appearance and behavior, executing complex tasks, particularly in replacing repetitive and hazardous labor. In 2023, the global humanoid robot market was valued at approximately $2.16 billion, with expectations to grow to $32.4 billion by 2029.
Intelligent Logistics: Growth of Autonomous Forklifts and Warehouse Robots
In the logistics field, embodied intelligent robots such as autonomous forklifts and warehouse robots are widely used to improve storage and transportation efficiency while reducing labor costs. It is projected that by 2030, the global humanoid robot market will reach $15.1 billion, with a compound annual growth rate (CAGR) exceeding 56% between 2024 and 2030, further driving the development of intelligent logistics robots.
Public Services: Deepening Application in Government, Healthcare, and Retail
Embodied intelligent robots are also increasingly being applied in public service fields. In the healthcare sector, surgical robots have been used to assist doctors in performing precise operations. In 2020, the global surgical robot market reached $83.21 million, with the U.S., Europe, and China as the top three markets, accounting for 55.1%, 21.4%, and 5.1% of the market share, respectively. Additionally, in government services and retail scenarios such as store guides, embodied robots are improving service quality and user experience.
Market Opportunities
The embodied AI systems market presents tremendous opportunities for growth and innovation across various industries. One of the most promising fields is the integration of embodied AI systems into the automotive industry. Embodied AI can enhance the capabilities of autonomous vehicles, enabling them to interact more naturally with passengers and respond effectively to dynamic driving environments. These systems can also improve Advanced Driver Assistance Systems (ADAS), providing real-time data processing and decision-making, thus enhancing vehicle safety and performance.
Another significant opportunity lies in the education sector, where embodied intelligent systems can transform the learning experience. AI-driven educational robots and virtual assistants can offer personalized tutoring, adapt to individual learning styles, and provide engaging educational content. These systems can also support teachers by automating administrative tasks and offering real-time insights into student performance.
In the entertainment industry, embodied systems are being explored for creating immersive interactive experiences. AI-driven characters and virtual assistants can enhance video games, virtual reality environments, and live performances by offering realistic interactions and personalized content.
In the industrial sector, embodied intelligent systems can optimize manufacturing processes, improve quality control, and enhance predictive maintenance. These systems can collaborate with human workers to perform repetitive or hazardous tasks, ensuring safety and efficiency in industrial operations.
With the continuous progress of AI and robotics technology, along with increasing investment and collaboration between tech companies and end-users, the adoption of embodied AI systems in emerging applications is expected to create substantial market opportunities in the coming years.
4.2 Challenges and Response Strategies
Data Privacy and Regulatory Challenges
As embodied intelligent robots are widely deployed, issues related to data privacy and security are becoming more prominent. Strict data protection laws (such as GDPR in Europe) limit the practical deployment of AI solutions, presenting challenges for AI solution providers.
To address this challenge, companies need to strengthen data protection measures to ensure user privacy is not violated, while actively collaborating with regulatory bodies to comply with relevant laws and regulations.
High Implementation Costs
The development, deployment, and maintenance costs of AI systems are high, which may exceed the long-term benefits of AI automation. This is especially challenging for small and medium-sized enterprises, as it creates a barrier to entry. To lower costs, businesses can focus on technological innovation, scale production, and collaborate with upstream and downstream supply chain companies to find cost optimization solutions.
Industry Ecosystem: Standardization and Supply Chain Integration
The development of embodied intelligent robots requires a sound industry ecosystem, including standardization and supply chain integration. Currently, the global humanoid robot industry chain has vast potential, and it may reach a trillion-dollar market scale in the future.
To promote healthy industry development, unified technical standards need to be established to ensure compatibility and interoperability between products from different manufacturers. Additionally, supply chain integration must be strengthened to ensure stable supply of key components.
Safety and Ethics: Data Privacy and Ethical Risks
The widespread use of embodied intelligent robots also presents safety and ethical challenges. In terms of data privacy, robots are required to process large amounts of user data, which could lead to privacy breaches. In terms of ethics, the robots' autonomous decision-making capabilities may spark ethical debates.
To address these concerns, relevant laws, regulations, and ethical guidelines should be developed to regulate the design, production, and use of robots, ensuring they align with societal moral and ethical standards.
4.3 Long-term Development Vision
How Embodied AI Will Change Human Work and Life
The popularization of embodied intelligent robots will profoundly change the way humans work and live. In the workplace, robots will take on more repetitive, dangerous, and high-precision tasks, improving productivity and allowing humans to engage in more creative work. In daily life, robots will become assistants, providing medical care, household services, and enhancing the quality of life.
Industry Transformation under Human-Robot Symbiosis Model
With the development of embodied intelligent robots, a human-robot symbiosis model will gradually take shape. Humans and robots will collaborate to complete complex tasks, driving the restructuring and upgrading of industries and creating new business models and job opportunities.
The Next 20 Years: From Automation to Autonomous Intelligence
Over the next 20 years, embodied intelligent robots will gradually transition from the current automation phase to an autonomous intelligence phase. With advancements in AI technology, robots will acquire stronger learning and adaptation abilities, enabling them to autonomously complete tasks in complex and dynamic environments. This will further expand the application scenarios for robots, driving profound changes in social production and lifestyles.
In conclusion, the future of embodied intelligent robots is full of opportunities and challenges. Through technological innovation, industry collaboration, and policy support, embodied intelligent robots will have a profound impact on human society and open a new chapter in intelligent development.
5. Conclusion
The embodied intelligent robot market is currently experiencing rapid growth, with an expected compound annual growth rate of over 20% in the next decade. This growth is primarily driven by the integration and advancement of technologies like AI, 5G, and the Internet of Things (IoT), which have accelerated the commercialization of intelligent robots. European and American companies dominate the high-end market with their technological advantages, while Chinese companies are quickly rising by leveraging cost advantages.
In the future, with further technological breakthroughs and increasing market demand, embodied intelligent robots will accelerate their penetration in sectors like industry, healthcare, logistics, and retail. However, core technological challenges such as perception, interaction, and motion control still need to be overcome. Additionally, issues like data privacy, regulatory concerns, high implementation costs, and industry ecosystem standardization will affect the development of the industry.
Overall, embodied intelligent robots are expected to profoundly change the way humans work and live, driving industrial transformation under a human-robot symbiosis model. Over the next 20 years, we will witness continued innovation and development in this field.
References
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