휴머노이드 로봇 기술 동향, 기회 요인 및 시장 전망 2025-2035
자동차 및 물류 산업을 중심으로 한 향후 10년간의 휴머노이드 로봇 시장 전망, 배터리, 액추에이터, 모터, 나사, 센서 등 휴머노이드 구성 부품, 주요 기업 동향, 휴머노이드 로봇 도입의 장애요인을 포함하여 향후 10년간 시장 전망을 포괄하는 보고서
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휴머노이드 로봇 시장, 기술, 그리고 주요 기업들을 다루고 있는 이 보고서에서는 자동차 및 물류 산업에서의 휴머노이드 활용, 핵심 부품에 대한 기술 분석, 2023~2024년의 과거 시장 데이터와 2025년부터 2035년까지의 시장 예측 및 전망을 제공합니다.
이 보고서는 휴머노이드 로봇의 주요 응용 분야와 각 구성 요소의 기술, 규제 및 상업적 과제에 초점을 맞춰 휴머노이드 로봇에 대해 아래와 같은 주요 정보를 제공합니다.
최신 휴머노이드 로봇, 대상 산업 및 도입 일정에 대한 검토
- 자동차 산업과 창고/물류 산업을 포함한 휴머노이드 로봇의 현재 작업과 활용 분야
- 각 산업 분야에서 중요한 기술에 대한 전반적인 개요
- 다양한 휴머노이드 로봇 기업에 대한 벤치마킹 및 분석
휴머노이드 로봇의 각 하드웨어 구성 요소에 대한 심층 분석
- 액추에이터, 모터, 감속기, 나사, 베어링, 카메라, LiDAR, 레이더 및 초음파 센서, 촉각 센서, 소프트웨어 및 AI, 배터리, 고성능 소재, 암 이펙터 등 구성요소의 기술적 분석 및 과제
- 구성 요소별 비용 분석
- 설계 및 제조상 도전 과제
- 규제 관련 과제
- 핵심 구성요소의 미래 동향 및 핵심 기술
시장 규모 전망 및 비즈니스 기회
- 자동차 산업 및 물류/창고 산업 전반의 휴머노이드 로봇 기업 리뷰
- 2023~2024년 휴머노이드 로봇 시장 데이터
- 2025~2035년 휴머노이드 로봇 비용 전망
- 자동차 산업 및 물류/창고 산업의 2025-2035년 시장 규모 및 도입량 예측
- 액추에이터, 모터, 감속기, 나사, 베어링, 카메라, LiDAR, 레이더 및 초음파 센서, 촉각 센서, 소프트웨어 및 AI, 배터리, 고성능 소재 및 암 이펙터 등 휴머노이드에 사용되는 주요 부품의 2025-2035년 시장 규모 및 채택량 예측
- 2025-2035년 휴머노이드 로봇의 배터리 용량 전망
이 보고서에서 다루는 주요 내용/목차는 아래와 같습니다.
1. 핵심 요약
2. 휴머노이드 로봇의 주요 고객 및 활용 사례
- 자동차 산업
- 물류 산업
- 휴머노이드 로봇 산업 주요 뉴스 및 기업
3. 설계, 제조, 규제 및 상업화 관련 과제
4. 부품 수준 분석
- 액추에이터
- 모터
- 감속기
- 나사
- 베어링
- 카메라, LiDAR, 레이더, 초음파 센서
- 촉각 센서
- 소프트웨어 및 AI
- 배터리
- 고성능 소재
- 암 이펙터
5. 시장 전망
- 향후 10년간 물류/창고 및 자동차 산업의 휴머노이드 로봇 시장 규모 전망
- 향후 10년간 물류/창고 및 자동차 산업의 휴머노이드 로봇 출하량 전망
- 향후 10년간 휴머노이드 로봇 단가 전망
- 향후 10년간 휴머노이드 로봇 배터리 용량 전망
- 향후 10년간 휴머노이드 로봇 구성 부품(액추에이터, 모터, 감속기, 나사, 베어링, 카메라, LiDAR, 레이더, 초음파 센서, 촉각 센서, 소프트웨어 및 AI, 배터리, 고성능 소재, 암 이펙터)의 단위/수량 전망
6. 기업 프로필
Humanoid robots are widely regarded as "Artificial Intelligence Embodied in the Real World," especially following the surge in AI advancements like ChatGPT over the past two years. From IDTechEx's research and analysis, the market has seen a surge in interest, with significant investments from flowing into leading startups such as Apptronik, Agility Robotics, Unitree, and Figure.AI. Further, massive players such as Tesla, Xiaomi, and Meta have also announced plans of getting into the humanoid robotics space.
IDTechEx's report, "Humanoid Robots 2025-2035: Technology, Market, and Opportunity," offers an in-depth technical analysis at the component level, covering actuators, motors, reducers, screws, bearings, cameras, LiDAR, radar, ultrasonic sensors, tactile sensors, AI-driven software, batteries, high-performance materials, and end effectors. This report provides a comprehensive look at the technologies, existing humanoid robots, design and manufacturing challenges, business and regulatory hurdles, and future market potential for humanoid robots, with a particular focus on opportunities in the automotive and logistics industries.
Key insights from the report include:
- A 10-year market size forecast for humanoid robots, segmented by the automotive and logistics/warehousing industries.
- A 10-year volume/unit forecast for humanoid robots across these industries.
- A 10-year market size forecast for humanoid robot hardware components, including actuators, motors, reducers, screws, bearings, cameras, LiDAR, radar, ultrasonic sensors, tactile sensors, batteries, and high-performance materials.
- A 10-year volume forecast for humanoid robot hardware components.
- A 10-year energy capacity (GWh) forecast for humanoid robot batteries.
- A 10-year forecast of the average selling price (ASP) of humanoid robots.
Industrial Applications: Automotive and Warehousing/Logistics
As of 2025, despite significant hype around humanoid robots, there are still limited real-world applications where they fit in. While many OEMs market their humanoid robots as general-purpose machines, IDTechEx split the target use cases into two categories, including: industrial and non-industrial applications.
Industrial humanoid robots, such as Tesla Optimus, Agility Robotics' Digit, and UBTech's Walker S, are typically heavier and equipped with larger battery packs, whereas non-industrial humanoids, like Unitree's G1, are more lightweight and designed for research or light-duty tasks with lower force/torque requirements.
Among industrial applications, the automotive and logistics/warehousing sectors have attracted the most interest. In the short to mid-term (before 2030), the automotive industry is expected to lead humanoid adoption, driven by factors such as the historic success of automation, large-scale production demands, and stronger cost negotiation power due to the big volume needed. Several automotive OEMs are already developing their own humanoid robots, including Tesla, Xiaomi, and XPeng. With well-established supply chains that overlap significantly with humanoid robotics, car manufacturers can leverage existing resources to reduce costs.
Tesla has announced plans to produce 5,000 Optimus robots, with potential scaling to 12,000 units based on production and supply chain readiness. BYD aims to deploy 1,500 humanoid robots in 2025, with a target of scaling up to 20,000 by 2026. Other leading automotive players, such as Mercedes-Benz (partnering with Apptronik) and BMW (collaborating with Figure.AI on Figure 02), are also making strides in humanoid robotics. Despite some targets seeming very aggressive and slightly unrealistic given the current supply chain status, investments and rapid developments highlight the industry's confidence in the future potential of humanoid robots.
However, as of 2025, humanoids in the automotive sector are still in the early pilot testing phase, primarily performing basic tasks like badge labeling, material handling, and inspection. IDTechEx analysts anticipate that by 2026-2027, humanoid robots will start operating for specific use cases, gradually expanding to more complex tasks between 2028 and 2033. This also means that general-purposed humanoid robots in other non-industrial area, such as healthcare, are even further away.
The logistics and warehousing industry also show promise for humanoid adoption, though progress has been slower. As of early 2025, IDTechEx has observed only a limited number of pilot projects, with fewer than 100 humanoids deployed in warehouses. Given that warehouse testing typically takes about 18 to 30 months, large-scale adoption (thousands of units) is unlikely before end of 2025. Additionally, warehouse operators must evaluate the return on investment and payback period for humanoid robots-an aspect still under assessment due to limited real-world deployments. With these reasons, IDTechEx believes that 2026-2027 would be the time that humanoids in logistics start taking off, primarily due to the proven successes from humanoids in the automotive industry.
Nonetheless, IDTechEx suggests that if humanoid robot prices drop to around US$20,000 and they can efficiently transport goods and perform basic pick-and-place tasks, interest could increase. Currently, achieving the same functionality with an autonomous mobile robot (AMR) or automated guided vehicle (AGV) combined with a robotic arm would cost significantly more than US$20,000, making humanoid robots a more attractive alternative to combine these two functions together.
Summary of humanoid robots by target application. For full data, refer to IDTechEx's research on "Humanoid Robots 2025-2035: Technology, Market, and Opportunity"
Component Challenges: Cost and Technical Hurdles
As of 2025, the average selling price of humanoid robots remains high. For instance, Tesla Optimus is estimated to cost between US$120,000 and US$150,000, largely due to expensive components and low production volumes. However, as production scales up, IDTechEx anticipates a steady decline in both component and overall humanoid costs.
Several technical and manufacturing challenges also persist at the component level. Key issues include:
- Battery capacity limitations, resulting in short operational times and high downtime.
- Production bottlenecks, such as the low volume of high-precision screws slowing down humanoid robot scaling.
- Dexterous hand development, requiring advanced tactile sensors to perform delicate tasks with precision.
Conclusion
While humanoid robots are still in their early stages of industrial deployment, their market potential is massive, especially in the automotive and logistics sectors. Significant investments, technological advancements, and increasing economies of scale are expected to drive rapid growth over the next decade. IDTechEx believes that the market size for humanoid robot will reach around US$30 billion by 2035, more details are in IDTechEx's latest research "Humanoid Robots 2025-2035: Technology, Market, and Opportunity".
Key Aspects
This report provides critical market intelligence about humanoid robots, focusing on their major applications and each component's technical, regulatory, and commercial challenges. This includes:
A review of state-of-the-art humanoids, their target industries, and adoption timeline.
- Current task and industry of humanoid robots, including automotive industry and warehousing/logistics industry
- General overview of important technologies within each sector
- Benchmarking and analysis of different humanoid robot players
Full analysis of each hardware component of the humanoid robot
- Technical analysis and challenges of components, including actuators, motors, reducers, screws, bearing, cameras, LiDAR, radar, and ultrasonic sensors, tactile sensors, software and AI, battery, high-performance materials, and arm effectors
- Cost analysis of different components
- Design and manufacturing challenges
- Regulatory challenges
- Future trends of critical components and key technologies to be used
Market size forecast and business opportunities throughout
- Reviews of humanoid robot players throughout the automotive industry and the logistics/warehousing industry
- Historic humanoid robot market data from 2023 to 2024
- Cost forecast of humanoid robot from 2025-2035.
- Market size and adoption volume forecasts from 2025-2035 for the automotive industry and logistics/warehousing industry
- Market size and adoption volume forecasts from 2025-2035 for main components used in humanoids, including actuators, motors, reducers, screws, bearing, cameras, LiDAR, radar, and ultrasonic sensors, tactile sensors, software and AI, battery, high-performance materials, and arm effectors
- Battery capacity forecast from 2025-2035 for humanoid robots
| Report Metrics | Details |
|---|---|
| Historic Data | To 2024 |
| CAGR | The global market for humanoid robots will increase with a CAGR of 32% from 2025 to 2035. |
| Forecast Period | 2025 - 2035 |
| Forecast Units | GWh, US$, unit |
| Regions Covered | Worldwide |
| Segments Covered | Actuators, motors, reducers, screws, bearing, cameras, LiDAR, radar, and ultrasonic sensors, tactile sensors, software and AI, battery, high-performance materials, and arm effectors. Automotive industry. Logistics and warehousing industry |
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추가 정보
이 보고서에 대해 궁금한 점이 있으시면 언제든지 research@IDTechEx.com으로 보고서 팀에 문의하거나, 영업 관리자에게 문의하십시오
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| 1. | EXECUTIVE SUMMARY |
| 1.1. | Pain Points and Trends of Humanoid Robots |
| 1.2. | Choice of components - cost-efficiency is the key? |
| 1.3. | Component trend - modularity, efficient materials, and power efficiency |
| 1.4. | Trend: Cost Reduction With Volume Upscaling and Universal Tasks |
| 1.5. | Summary of humanoid robots |
| 1.6. | Maturity of commercialization of humanoid robots by application |
| 1.7. | Summary of critical hardware components in humanoid robots |
| 1.8. | Actuator - technical comparison and challenges |
| 1.9. | Summary of motors |
| 1.10. | Benchmarking reducers |
| 1.11. | 3D visual systems to sense surroundings |
| 1.12. | Benchmarking tactile sensors by technology |
| 1.13. | Cost analysis by component |
| 1.14. | Summary of software and functions |
| 1.15. | Humanoids market by country and primary use-case |
| 1.16. | Benefits and challenges of humanoid robots in the logistics industry |
| 1.17. | Estimated timeline of tasks handled by humanoid robots in the logistics industry |
| 1.18. | Humanoid robot tasks in the automotive industry: near established vs. emerging applications |
| 1.19. | Ambitious goals of humanoid deployment from BYD and Tesla |
| 1.20. | Technical Challenges for Humanoid Robots in the Automotive Industry |
| 1.21. | Commercial and regulatory challenges for humanoids in automotive industry |
| 1.22. | Market size and volume forecast of humanoid robots in the automotive and logistics industry |
| 1.23. | Battery capacity (GWh) forecast for humanoid robots used for industries: 2025-2035 |
| 1.24. | Humanoid robot hardware component volume forecast: 2025-2035 |
| 1.25. | Humanoid robot hardware component market size forecast: 2025-2035 |
| 2. | INTRODUCTION |
| 2.1. | Humanoid Robotics Overview |
| 2.2. | Why humanoid robots and what is the difference between humanoid robots and specialized robots? |
| 2.3. | What is accelerating the adoption of humanoid robots? |
| 2.4. | What is holding back the adoption of humanoid robots? |
| 2.5. | Over 1 billion humanoid robots by 2040 - Comments from Elon Musk |
| 2.6. | A fast-growing humanoid robotics industry |
| 2.7. | Leading players enter the space of humanoid robotics |
| 2.8. | Key catalyst events summary |
| 2.9. | Cosmos and Nvidia's Isaac GR00T |
| 2.10. | Synergies between automotive industry and humanoid robotics industry |
| 2.11. | Cost analysis - Optimus (1/2) |
| 2.12. | Cost analysis - Optimus (2/2) |
| 2.13. | Partnerships and adoption |
| 3. | MAJOR CUSTOMERS AND USE CASES |
| 3.1. | Overview |
| 3.1.1. | Sectors that most likely to adopt humanoid robot (1/2) |
| 3.1.2. | Sectors that most likely to adopt humanoid robot (2/2) - fast growth in 2024 |
| 3.1.3. | Humanoids market by country and primary use-case |
| 3.1.4. | Maturity of commercialization of humanoid robots by application |
| 3.1.5. | Summary of humanoid robots (1/3) |
| 3.1.6. | Summary of humanoid robots (2/3) |
| 3.1.7. | Summary of humanoid robots (3/3) |
| 3.2. | Automotive industry |
| 3.2.1. | Automotive industry - collaborations (1/2) |
| 3.2.2. | Automotive industry - collaborations (2/2) |
| 3.2.3. | Humanoid robots and automotive OEMs (1/2) |
| 3.2.4. | Humanoid robots and automotive OEMs (2/2) |
| 3.2.5. | Tasks of humanoid robots in automotive industry |
| 3.2.6. | Automotive - UBTech's humanoids used for materials handling at BYD |
| 3.2.7. | Automotive - Nio uses UBTech's humanoid doing pilot operation at factories |
| 3.2.8. | Zeekr also followed Nio to deploy UBTech's humanoids in their factories |
| 3.2.9. | Figure AI's Figure 02 works with BMW |
| 3.2.10. | Apptronik's Apollo with Mercedes-Benz |
| 3.2.11. | Humanoid Robot Tasks in the Automotive Industry: Near Established vs. Emerging Applications |
| 3.2.12. | Ambitious goals of humanoids deployment from BYD and Tesla |
| 3.2.13. | Technical Challenges for Humanoid Robots in the Automotive Industry |
| 3.2.14. | Commercial and regulatory challenges for humanoids in automotive industry |
| 3.2.15. | Opportunities for humanoids in automotive industry |
| 3.3. | Logistics industry |
| 3.3.1. | Introduction to humanoid robots in logistics industry |
| 3.3.2. | Benefits and challenges of humanoid robots in the logistics industry |
| 3.3.3. | Agility Robotics - Leading Humanoid Robot Player in the Logistics Industry |
| 3.3.4. | Cooperative area for humanoid robots used in warehouses - safety challenge |
| 3.3.5. | BYD - UBTech's last mile delivery with humanoid robots |
| 3.3.6. | GXO and Apptronik |
| 3.3.7. | Figure's Helix: Humanoid Robotics in Logistics |
| 3.3.8. | Estimated timeline of tasks handled by humanoid robots in the logistics industry |
| 3.4. | News and players involved in humanoid robotics industry |
| 3.4.1. | Meta getting into humanoid robot |
| 3.4.2. | Nvidia's Humanoid Robot Technologies |
| 3.4.3. | Cosmos and Nvidia's Isaac GR00T |
| 3.4.4. | Apptronik raised US$350 million in series A funding |
| 4. | DESIGN, MANUFACTURING, AND COMMERCIAL CHALLENGES |
| 4.1. | Summary of challenges |
| 4.1.1. | Design and manufacturing challenges (1/3) - Summary |
| 4.1.2. | Design and manufacturing challenges (2/3) - Summary |
| 4.1.3. | Design and manufacturing challenges (3/3) - Summary |
| 4.1.4. | Commercial and social barriers for adopting humanoid robots |
| 4.1.5. | Challenges around humanoid robot integration |
| 4.1.6. | UniTree |
| 4.1.7. | Manus - MetaGloves for Hand-Tracking for Motion Capture |
| 4.2. | Design and manufacturing challenges |
| 4.2.1. | Design and manufacturing challenges - actuators (motors + reducers) |
| 4.2.2. | Design and manufacturing challenges - reducers |
| 4.2.3. | Design and manufacturing challenges - motors and thermal management (1/2) |
| 4.2.4. | Design and manufacturing challenges - motors and thermal management (2/2) |
| 4.2.5. | Design and manufacturing challenges - batteries and cooling |
| 4.2.6. | Design, manufacturing, and commercial challenges - tactile sensors |
| 4.3. | Regulatory and commercial challenges |
| 4.3.1. | Concerns: safety, regulation, and data privacy |
| 4.3.2. | How to work around safety and regulatory requirement - cooperative space for industrial settings |
| 4.3.3. | Lack of enough evidence to prove the return on investment |
| 4.3.4. | Regional regulations for humanoid robots |
| 5. | COMPONENT LEVEL ANALYSIS |
| 5.1. | Overview |
| 5.1.1. | Component summary of humanoid models |
| 5.1.2. | Summary of critical components in humanoid robots |
| 5.1.3. | Cost analysis by component |
| 5.1.4. | Component overview - Tesla Optimus |
| 5.1.5. | Component overview - Unitree G1 |
| 5.2. | Actuators Overview |
| 5.2.1. | Actuators - introduction |
| 5.2.2. | Actuators - componentry level split |
| 5.2.3. | Actuators categorization: linear and rotary |
| 5.2.4. | Linear and rotary actuators and their pros and cons |
| 5.2.5. | Linear and rotary actuators and their applications in humanoids' joints |
| 5.2.6. | Actuator categorization: electric, pneumatic and hydraulic |
| 5.2.7. | Actuator - technical comparison and challenges |
| 5.2.8. | Actuation: direct drive or geared setting? |
| 5.3. | Motors |
| 5.3.1. | Electric motors are getting increasingly popular |
| 5.3.2. | A summary of motors for different humanoid robotics companies |
| 5.3.3. | Direct drive motors - frameless motors |
| 5.3.4. | Frameless motors - can be used for direct drive actuator or geared actuation |
| 5.3.5. | Brushed/Brushless motors |
| 5.3.6. | Coreless motors - type of brushed motors |
| 5.3.7. | Benefits and drawbacks of coreless motors |
| 5.3.8. | Summary of motors |
| 5.3.9. | Use case: Tesla Optimus motors |
| 5.4. | Reducers |
| 5.4.1. | Reducer Overview: Harmonic, Planetary, and RV Reducers |
| 5.4.2. | Benchmarking Reducers (1/2) |
| 5.4.3. | Benchmarking Reducers (2/2) |
| 5.4.4. | Harmonic reducer |
| 5.4.5. | Design, manufacturing and material challenges of harmonic reducers |
| 5.4.6. | RV Reducer |
| 5.4.7. | Design, manufacturing and material challenges of RV reducers |
| 5.4.8. | Planetary reducer |
| 5.4.9. | Thermal management challenges of planetary reducers |
| 5.4.10. | Design and manufacturing challenges of planetary reducers |
| 5.4.11. | Use cases: Tesla Optimus |
| 5.5. | Screws |
| 5.5.1. | Introduction to different types of screws |
| 5.5.2. | Ball screws - component and technical analysis (1/2) |
| 5.5.3. | Ball screws - component and technical analysis (2/2) |
| 5.5.4. | Planetary roller screws - introduction and key components |
| 5.5.5. | Planetary roller screws benefits and drawbacks |
| 5.5.6. | Challenge of planetary roller screws: manufacturing with high quality at large scale |
| 5.5.7. | Material considerations of planetary roller screws |
| 5.5.8. | Tesla Optimus: roller screws and ball screws |
| 5.5.9. | Future trend of screws for heavy-duty tasks |
| 5.6. | Bearing |
| 5.6.1. | Introduction to bearings |
| 5.6.2. | Categorization of bearings |
| 5.6.3. | Comparison of ball bearing and roller bearing |
| 5.7. | Sensors - cameras, LiDAR, radar, and ultrasonic sensors |
| 5.7.1. | 3D visual systems to sense the surroundings |
| 5.7.2. | Use Case: Tesla Optimus Camera |
| 5.7.3. | Use Case: UBTech's Walker S1 with multi-cameras |
| 5.7.4. | Use Case: UBTech's Walker X with multi-cameras and ultrasonic sensors |
| 5.7.5. | Use Case: Boston Dynamics: LiDAR, depth sensor and RGB camera |
| 5.7.6. | Pure Camera or LiDAR + Camera Solution? |
| 5.7.7. | Outlook: cameras and LiDAR in humanoid robots |
| 5.7.8. | Comparison of LiDAR, cameras, and 1D/3D ultrasonic sensors |
| 5.7.9. | Comparisons of LiDAR, camera & ultrasonic sensors - (1) |
| 5.7.10. | Comparisons of LiDAR, camera & ultrasonic sensors - (2) |
| 5.7.11. | LiDAR costs and technical analysis for uses in humanoid robots |
| 5.7.12. | Necessity and categorization of LiDAR in humanoids |
| 5.7.13. | LiDAR cost breakdown and scanning methods |
| 5.7.14. | mmWave Radar |
| 5.8. | Tactile Sensors |
| 5.8.1. | Tactile sensors - introduction to the technologies behind the sensors |
| 5.8.2. | Tactile sensors - high value components for humanoid robotics |
| 5.8.3. | Benchmarking tactile sensors by technology |
| 5.8.4. | Use Case: Tactile Sensors into Sanctuary.AI's Phoenix General Purpose Robots |
| 5.8.5. | Use Case: 6D Tactile/Force Sensors into Tesla's Optimus |
| 5.8.6. | Paxini - Tactile sensors for humanoid robot fingers |
| 5.8.7. | Comparison of Paxini's tactile sensors with traditional tactile sensors |
| 5.8.8. | Unitree uses Nexdor and Hanwei's tactile sensors |
| 5.8.9. | Gelsight - Digit: camera-based tactile sensor for hands |
| 5.8.10. | Flexible tactile is the trend, however, technical and material challenges remain |
| 5.8.11. | Tactile sensing on hands and feet |
| 5.8.12. | Tactile sensing and e-skins on body |
| 5.8.13. | Challenges of tactile sensors and electronic skins |
| 5.8.14. | Summary of tactile sensors |
| 5.9. | Software, AI and Chips |
| 5.9.1. | AI hardware and software introduction |
| 5.9.2. | Summary of software and functions |
| 5.9.3. | Software - Simulation/training environments and perception/sensing |
| 5.9.4. | Software - motion planning and control |
| 5.9.5. | Software - foundation model |
| 5.9.6. | Lack of training data - pain points of AI - synthetic data generation |
| 5.9.7. | Nvidia Isaac GR00T - synthetic data generation |
| 5.9.8. | Multi-contact planning and control for humanoid robots |
| 5.10. | Batteries and power electronics for charging |
| 5.10.1. | Humanoid's batteries - parameters comparison |
| 5.10.2. | Challenges of batteries |
| 5.10.3. | Limited battery endurance - fast charging or battery swapping - thermal management challenges and potential solutions |
| 5.10.4. | Swappable battery that runs for four hours continuously |
| 5.10.5. | Outlook for batteries in humanoids |
| 5.10.6. | Battery capacity per humanoid robot for industrial applications forecast: 2025-2045 |
| 5.11. | High-performance materials |
| 5.11.1. | Shape Metal Alloys |
| 5.11.2. | Magnesium alloy - trend towards lightweight humanoid robot |
| 5.11.3. | Technical challenges of magnesium alloy and Honda's ASIMO |
| 5.11.4. | PEEK - costs and technical properties |
| 5.11.5. | Applications of PEEK in Humanoid Robot Components |
| 5.11.6. | Challenges and market outlook for PEEK in humanoid robots |
| 5.11.7. | Commercial PEEK materials that can be used for humanoids |
| 5.11.8. | Material performance comparison of PEEK, aluminum and magnesium alloy |
| 5.11.9. | NdFeB - rare earth permanent magnets |
| 5.11.10. | Rare earth metals are commonly used in electric vehicles, leading to supply chain synergies to humanoid robotics industry |
| 5.11.11. | Ultra High Molecular Weight Polyethylene (UHMWPE) |
| 5.11.12. | Steel materials for humanoid robots - estimated gravimetric requirement per type of material for Optimus |
| 5.11.13. | Summary of material preference for humanoid robot |
| 5.12. | Arm Effectors |
| 5.12.1. | Key points of humanoid's arm effectors |
| 5.12.2. | Hot swappable arm effectors |
| 5.12.3. | Technical barriers of humanoid's hands |
| 5.12.4. | Actuation methods of humanoid's hands |
| 6. | MARKET FORECASTS AND FUTURE TRENDS |
| 6.1. | Market size forecast of humanoid robots in the automotive industry: 2025-2035 |
| 6.2. | Volume forecast of humanoid robots in the automotive industry: 2025-2035 |
| 6.3. | Volume forecast of humanoid robots in the logistics and warehousing industry: 2025-2035 |
| 6.4. | Market size forecast of humanoid robots in the logistics and warehousing industry: 2025-2035 |
| 6.5. | Cost forecast of humanoid robot: 2025-2035 |
| 6.6. | Battery capacity (GWh) forecast for humanoid robots used for industries: 2025-2035 |
| 6.7. | Humanoid robot hardware component volume forecast: 2025-2035 |
| 6.8. | Humanoid robot hardware component market size forecast: 2025-2035 |
| 7. | PROFILES |
Ordering Information
휴머노이드 로봇 기술 동향, 기회 요인 및 시장 전망 2025-2035
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휴머노이드 로봇 시장 규모는 2035년까지 약 300억 달러에 이를 것으로 전망
보고서 통계
| 슬라이드 | 235 |
|---|---|
| 전망 | 2035 |
| 게시 | Apr 2025 |
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