市場調査レポート

商品コード

1749731

産業用ロボットの世界市場（2026年～2046年）

The Global Industrial Robots Market 2026-2046

出版日: 2025年06月16日
発行: Future Markets, Inc.
ページ情報: 英文 554 Pages, 218 Tables, 59 Figures
納期: 即納可能

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概要
図表
目次

概要

サンプル依頼リストに入れる

産業用ロボット市場は劇的に変化し、ケージに囲まれた単純な機械から、従来式産業用ロボット、協働ロボット（コボット）、ヒューマノイドロボット、インテリジェントモバイルシステムを含む洗練されたエコシステムへと進化しています。この拡大した情勢は、多様な産業用途において、人間の作業者と先進ロボット技術をシームレスに統合する、柔軟で適応力のあるオートメーションへと向かう製造のシフトを反映しています。今日の産業用ロボット市場は複数のカテゴリにまたがっており、それぞれが特定の製造ニーズに対応しています。従来式産業用ロボットは、自動車の溶接や電子機器の組み立てのような多数・高精度の用途を独占し続けています。しかし、協働ロボットは、防護壁なしで人間の作業者と一緒に安全に作業できるように設計された、ゲームチェンジャーとなるセグメントとして台頭しています。これらのコボットは、先進の力制限技術、速度モニタリングシステム、迅速な展開と再構成を可能にする直感的なプログラミングインターフェースを特徴としています。

ヒューマノイドロボットは、市場でもっとも野心的なフロンティアであり、複雑な製造作業に人間のような器用さと機動性を提供します。Boston Dynamics、Figure AI、Agility Roboticsなどの企業は、標準的な産業環境を移動し、多様な物体を操作し、多段階の組み立て工程を実行できる二足歩行ヒューマノイドシステムを開発しています。これらのシステムは、従来の固定式ロボットには複雑すぎる作業をこなしながら、労働力不足に対処することが期待されています。

自律走行搬送ロボット（AMR）とモバイルマニピュレーターは、機動性と操作能力を兼ね備え、変化する生産レイアウトに適応できる柔軟な自動化ソリューションを生み出します。これらのシステムは、先進のSLAM（Simultaneous Localization and Mapping）技術、LiDARセンサー、AIを搭載したナビゲーションを活用し、人間の作業者とともに動的な環境で安全に動作します。

技術の融合とAIの統合：AIの統合は、産業用ロボットの能力を根本的に変えました。最新のシステムには、リアルタイムの品質検査、物体認識、適応型組み立てに用いるコンピュータービジョンが組み込まれています。機械学習アルゴリズムは、ロボットが継続的にパフォーマンスを最適化することを可能にし、生産変動から学習し、時間の経過とともに精度を向上させます。マルチモーダルAIシステムは、視覚、力覚、音声処理を組み合わせることで、先進の意思決定が可能なロボットを実現します。

エッジコンピューティングは、ロボットがセンサーデータをローカルで分析し、状況の変化に即座に対応できるようにするリアルタイム処理に不可欠となっています。この機能は、人間の存在や予期せぬ障害物に即座に対応することが安全上要求される共同作業用途において特に重要です。先進のセンサーフュージョンは、カメラ、LiDAR、力センサー、近接センサーからのデータを組み合わせて、包括的な環境認識を実現します。

自動車産業は依然として産業用ロボットをもっとも多く採用しており、最終組み立て作業にはコボット、複雑な配線や内装部品の取り付けにはヒューマノイドロボットの展開が進んでいます。電子機器製造では、繊細なコンポーネントのハンドリングやテスト工程に協働ロボットが採用され、ヒューマノイドシステムは人間のような器用さを必要とするスマートフォンやタブレットの組み立てに有望視されています。食品・飲料加工では、包装、品質検査、マテリアルハンドリングに先進ロボットの活用が進んでいます。協働ロボットは、柔軟性と簡単な清掃が不可欠な食品調理や包装の用途に優れています。医薬品製造では、無菌ハンドリング、精密な分注、医療機器の複雑な組み立てにこうした技術が採用されています。

労働者不足は引き続き市場成長の促進要因となっており、特に人型ロボットは、航空宇宙や造船などの産業における熟練労働者の不足を解消するのに適しています。先進国では労働力の高齢化が進んでおり、経験豊富な作業者が監督や品質管理に専念する一方で、ロボットが肉体的に負荷のかかる作業を行う機会が生まれています。

当レポートでは、世界の産業用ロボット市場について調査分析し、各セグメントの市場規模と成長予測、技術情勢と技術革新の動向、企業プロファイルと競合情勢などの情報を提供しています。

市場のセグメンテーション
- ロボットタイプ別
- 技術別
- コンポーネント別
- 最終用途産業別
地域市場の分析
- 北米
- 欧州
- 日本
- 中国
- インド
価格分析とコスト構造
- コスト分析：ロボットタイプ別
- コスト分析：コンポーネント別
- 回収期間/ROI：用途別
- パラメーターの比較 - 積載量 vs. 最高移動速度

第4章技術の情勢

協働ロボット（コボット）
自律走行搬送ロボット（AMR）
ヒューマノイド産業用ロボット
モバイルロボット
ロボットアーム
ロボットグリッパー
ソフトウェア・コントロール
支援システム

第5章技術コンポーネントとサブシステム

AIと制御システム
センサーと知覚

第6章最終用途産業の分析

自動車
電子
食品・飲料
製薬
新興産業用途

第7章市場促進要因と抑制要因

市場促進要因
- 労働力不足と賃金インフレ
- 生産性と効率性の需要
- 品質と精度の要件
- 職場の安全性に関する懸念
- 高齢化
- AIと機械学習の進歩
- パーソナルアシスタンスと交友へのニーズ
- 危険で過酷な環境の探査
- eコマースの成長
市場抑制要因
- 高い初期投資費用
- 技術的な制限
- 実装上の課題
- 安全性と規制に関する懸念
- 労働者の抵抗と社会的受容

第8章新たな動向と発展

スウォームロボティクス
人間とロボットの協働
自己学習型・適応型ロボット
クラウドロボティクス
デジタルツイン統合
RaaS（Robot-as-a-Service）ビジネスモデル
ソフトロボティクス
ロボティクス向けニューロモルフィックコンピューティング
マイクロナノロボット
ブレインコンピューターインターフェース
モバイルコボット
インダストリー5.0と協働ロボット
低炭素ロボット製造
自律航法と位置特定
自動運転車に駆動されるナビゲーションセンサー

第9章課題と機会

技術的課題
市場の課題
規制上の課題

第10章将来の見通し

技術ロードマップ（2025年～2046年）
産業の融合の機会
ロボティクスと労働の未来

第11章企業プロファイル（企業120社のプロファイル）

第12章参考文献

図表

List of Tables

Table 1. Robot Categorization
Table 2. Global Unit Sales Forecast 2023-2046 (Million Units), Total
Table 3. Global Unit Sales Forecast 2023-2046 (Million USD)
Table 4. Key Market Drivers and Restraints for Advanced Robotics
Table 5. Robot Density in Manufacturing 2020-2024
Table 6. Growth of Robot Users 2020-2024
Table 7. Growth of Robot Stock by Sector 2020-2024
Table 8. Performance Parameters of Humanoid Robots
Table 9. Three Phases of Cobot Adoption
Table 10. Six Stages of Human-Robot Interaction (HRI)
Table 11. Traditional Industrial Robots vs. Collaborative Robots
Table 12. Benefits and Drawbacks of Cobots
Table 13. Safety Requirements for Cobots
Table 14. Comparison of Sensing Technologies
Table 15. Navigation Sensors for Autonomous Mobility
Table 16. Parameter Comparison - Payload vs. Speed
Table 17. Leading Companies by Robot Type
Table 18. Major Industrial Robot Manufacturers
Table 19. Service Robot Companies
Table 20. Collaborative Robot (Cobot) Manufacturer
Table 21. AI Robotics Companies
Table 22. Sensor and Component Developers
Table 23. End Effector Suppliers
Table 24. Humanoid Robot Developers
Table 25. Global Robotics Investment by Funding Category 2015-2024 (Billions USD)
Table 26. Industrial Robotics Funding by Technology Type 2014-2024
Table 27. Recent investments in advanced robotics companies
Table 28. Venture Capital Funding of Robotics Startups
Table 29. Classification of Robot Types
Table 30. Three Phases of Robot Adoption
Table 31. Evolution from Industrial to Service Robots
Table 32. Key AI Methods for Robotics
Table 33. Deep Learning Approaches
Table 34. Convolutional Neural Networks in Robotics
Table 35. Image Recognition Technologies
Table 36. Multi-sensor Integration in Advanced Robotics
Table 37. Advanced Materials in Advanced Robotics
Table 38. Types of metals commonly used in advanced robots
Table 39. Types of plastics and polymers commonly used in advanced robots
Table 40. Types of composites commonly used in advanced robots
Table 41. Types of elastomers commonly used in advanced robots
Table 42. Types of smart materials in advanced robotics
Table 43. Types of textiles commonly used in advanced robots
Table 44. Types of ceramics commonly used in advanced robots
Table 45. Biomaterials commonly used in advanced robotics
Table 46. Types of nanomaterials used in advanced robotics
Table 47. Types of coatings used in advanced robotics
Table 48. Flexible and soft materials
Table 49. Edge Computing in Advanced Robotics
Table 50. Local Processing vs. Cloud Computing
Table 51. Typical Sensors for Object Detection
Table 52. Camera-based Detection Technologies for Advanced Robotics
Table 53. LiDAR-based Detection Technologies for Advanced Robotics
Table 54. Radar Systems for Advanced Robotics Object Detection
Table 55. Ultrasonic Sensor Technologies for Advanced Robotics
Table 56. Infrared and Thermal Sensor Technologies for Advanced Robotics
Table 57. Technology Maturity Status Definitions
Table 58. Readiness Level of Technologies by Application Sector
Table 59. Regional Safety Standards in North America
Table 60. Regional Safety Standards in Europe
Table 61. Regional Safety Standards in Europe
Table 62. Authorities Regulating Autonomous Driving
Table 63. Regulations for Delivery Robots and Drones
Table 64. Industrial Robot Regulations
Table 65. Data Privacy and Security Regulations
Table 66. Regional Differences in Regulations
Table 67. Data Security Requirements
Table 68. Global Market for Industrial Robots 2020-2046 (Million Units)
Table 69. Global market for industrial robots 2020-2046 (Millions USD)
Table 70. Global market for Cobots by revenues 2025-2046 (US$ Millions)
Table 71. Global market for Cobots by payload capacity 2025-2046 (US$ Millions)
Table 72. Global market for Cobots By Degrees of Freedom 2025-2046 (US$ Millions)
Table 73. Global market for Cobots By End-Effector Type 2025-2046(US$ Millions)
Table 74. Global market for Humanoid Robots by type 2025-2046 (Million Units)
Table 75. Global market for Humanoid Robots by Application 2025-2046 (Million Units)
Table 76. Global Market for Mobile Robots 2020-2046 (Millions USD)
Table 77. Global Market for Autonomous Mobile Robots (AMRs) 2025-2046 (Million Units)
Table 78. Global Market for Automated Guided Vehicles (AGVs) 2025-2046 (Million Units)
Table 79. Global Market for Grid-Based Automated Guided Carts (AGCs) 2025-2046 (Million Units)
Table 80. Global Market for Mobile Picking Robots 2025-2046 (Million Units)
Table 81. Global Market for Mobile Manipulators 2025-2046 (Million Units)
Table 82. Global Market for Last-Mile Delivery Robots 2025-2046 (Million Units)
Table 83. Global Market for Heavy-Duty L4 Autonomous Trucks 2025-2046 (Million Units)
Table 84. Global Market for Robotics Navigation and Mapping 2025-2046 (Billions USD)
Table 85. Global Market for Robotics Object Recognition and Tracking 2025-2046 (Billions USD)
Table 86. Global Market for Robotics Manipulation Technologies 2025-2046 (Billions USD)
Table 87. Global Market for Human-Robot Interaction Technologies 2025-2046
Table 88. Global Market for Robotics Artificial Intelligence 2025-2046 (Billions USD)
Table 89. Global Market for Robotics Sensors 2025-2046 (Billions USD)
Table 90. Global Market for Robotics Actuators 2025-2046 (Billions USD)
Table 91. Global Market for Robotics Power Systems 2025-2046 (Billions USD)
Table 92. Global Market for Robotics Control Systems 2025-2046 (Billions USD)
Table 93. Global Market for Robotics End-Effectors 2025-2046 (Billions USD)
Table 94. Global Market for Robotics Control Software 2025-2046 (Billions USD)
Table 95. Global Market for Robotics Perception Software 2025-2046 (Billions USD)
Table 96. Global Market for Robotics Human-Machine Interfaces 2025-2046 (Billions USD)
Table 97. Global Market for Robotics Installation and Integration Services 2025-2046 (Billions USD)
Table 98. Global Market for Robotics Maintenance and Support Services 2025-2046 (Billions USD)
Table 99. Global Market for Advanced Robotics in Manufacturing 2025-2046 (Thousands of Units)
Table 100. Global Market for Advanced Robotics in Logistics and Warehousing 2025-2046 (Thousands of Units)
Table 101. Market for Advanced Robotics in North America 2020-2046 (1000 units, by Robot Type)
Table 102. Market for Advanced Robotics in Europe 2020-2046 (1000 units, by Robot Type)
Table 103. Market for Advanced Robotics in Japan 2020-2046 (1000 units, by Robot Type)
Table 104. Market for Advanced Robotics in China 2020-2046 (1000 units, by Robot Type)
Table 105. Market for Advanced Robotics in China 2020-2046 (1000 units, by End-Use Industry)
Table 106. Market for Advanced Robotics in India 2020-2046 (1000 units, by Robot Type)
Table 107. Average Cost per Unit for Industrial Robots 2025-2046 (Thousands USD)
Table 108. Average Cost per Unit for Collaborative Robots 2025-2046 (Thousands USD)
Table 109. Average Cost per Unit for Service Robots 2025-2046 (Thousands USD)
Table 110. Average Cost per Unit for Humanoid Robots 2025-2046 (Thousands USD)
Table 111. Average Cost per Unit for Mobile Robots 2025-2046 (Thousands USD)
Table 112. Average Cost for Robot Sensor Packages 2025-2046 (Thousands USD)
Table 113. Average Cost for Robot Actuator and Power Systems 2025-2046 (Thousands USD)
Table 114. Average Cost for Robot Computing and Control Systems 2025-2046 (Thousands USD)
Table 115. Average Cost for Robot End-Effectors 2025-2046 (Thousands USD)
Table 116. Payback Time for Advanced Robotics in Manufacturing 2025-2046 (Months)
Table 117. Payback Time for Advanced Robotics in Logistics 2025-2046 (Months)
Table 118. Payload and Speed Capabilities by Robot Type 2025-2046
Table 119. Key Performance Metrics for Industrial Robots 2025-2046
Table 120. Mobile Robots Performance Metrics
Table 121. Key Performance Metrics for Collaborative Robots 2025-2046
Table 122. Six Stages of Human-Robot Interaction (HRI)
Table 123. Benefits and Drawbacks of Cobots
Table 124. Safety Requirements for Cobots
Table 125. Cobot Cost Analysis
Table 126. Payload Summary of Cobots
Table 127. Commercialized Cobots
Table 128. Benchmarking Based on DoF, Payload, Weight
Table 129. Price Categories of Cobots
Table 130. Market Players in Collaborative Robots (Cobots)
Table 131. AMR Navigation Technologies
Table 132. Applications in Manufacturing for Humanoid Industrial Robots
Table 133. Design Considerations for Humanoid Industrial Robots
Table 134. Market Players in Humanoid Robots
Table 135. Market Players in Mobile Robots
Table 136. Articulated Robots Types and Applications
Table 137. SCARA Robots Market Overview
Table 138. Delta Robots Market Overview
Table 139. Cartesian (Gantry) Robots Market Overview
Table 140. Market Players in Robotic Arms (Delta, Cartesian/Gantry, SCARA)
Table 141. Market Players in Robotic Grippers
Table 142. Robot Software and Control Systems Market Overview
Table 143. Rails Market Overview
Table 144. Actuators for Cartesian Robots Market Overview
Table 145. Market Players in Linear Motion Systems
Table 146. Vision Systems Market Overview
Table 147. Industrial Cameras Market Overview
Table 148. LiDAR Market Overview
Table 149. Sensors for Guidance/QC Market Overview
Table 150. Vision Systems Market Players
Table 151. AI Applications in Robotics
Table 152. Machine Learning Techniques for Robotics
Table 153. Typical Sensors Used for Robots
Table 154. Sensors by Functions and Tasks
Table 155. Sensors for Industrial Robotic Arms
Table 156. Sensors for AGVs and AMRs
Table 157. Sensors for Collaborative Robots
Table 158. Sensors for Drones
Table 159. Sensors for Service Robots
Table 160. Sensors for Underwater Robots
Table 161. Sensors for Agricultural Robots
Table 162. Sensors for Cleaning Robots
Table 163. Sensors for Social Robots
Table 164. Cameras (RGB, Depth, Thermal, Event-based)
Table 165. RGB/Visible Light Cameras
Table 166. Depth cameras
Table 167. Thermal cameras
Table 168. Event-based cameras
Table 169. CMOS Image Sensors vs. CCD Cameras
Table 170. Edge Processing Technologies for Robotic Vision
Table 171. In-camera Computer Vision in Autonomous Vehicles
Table 172. Automotive Industry Robotics Opportunities and Challenges
Table 173. Advanced Robotics Applications in Automotive Manufacturing
Table 174. Miniaturization Challenges and Robotic Solutions in Electronics Manufacturing
Table 175. Production Volume Challenges in Electronics Manufacturing
Table 176. Quality Control Challenges in Electronics Manufacturing
Table 177. Advanced Robotics in Electronics Component Assembly
Table 178. Advanced Robotics in Electronics Testing and Inspection
Table 179. Advanced Robotics in Electronics Packaging
Table 180. Hygiene and Safety Requirements for Food Robotics
Table 181. Product Variety Challenges in Food Robotics
Table 182. Applications of Advanced Robots in Palletizing
Table 183. Industry Requirements for Pharmaceutical Robotics
Table 184. Applications of Advanced Robotics in Pharmaceuticals
Table 185. Key Technologies for Additive Manufacturing Integration
Table 186. Companies Implementing Additive Manufacturing Integration
Table 187. Key Technologies for Flexible Manufacturing Systems
Table 188. Companies Implementing Flexible Manufacturing Systems
Table 189. Key Technologies Enabling Lights-Out Manufacturing
Table 190. Companies Implementing Lights-Out Manufacturing
Table 191. Key Technologies for Mass Customization Robotics
Table 192. Companies Implementing Mass Customization Robotics
Table 193. Swarm Robotics: Technologies and Approaches
Table 194. Market Implementation Examples for Human-Robot Collaboration
Table 195. Reinforcement Learning Applications for Self-Learning and Adaptive Robots
Table 196. Robot-as-a-Service (RaaS) Subscription-based services
Table 197. Pay-per-use models
Table 198. Market adoption of Robot-as-a-Service
Table 199. Materials and actuators
Table 200. Control systems for soft robots
Table 201. Brain-inspired computing architectures
Table 202. Applications in Perception
Table 203. Neuromorphic computing Energy Efficiency Benefits
Table 204. Micro-nano robots medical applications
Table 205. Industrial Applications of Micro-Nano Robots
Table 206. BCIs in Robot Control Applications
Table 207. Technologies and Designs in Mobile Cobots
Table 208. Mobile Cobots in Industry
Table 209. Sustainable Manufacturing
Table 210. Implementation Examples
Table 211. Sustainable Design Approaches in Low-Carbon Robotics Manufacturing
Table 212. SLAM Advancements in Autonomous Navigation and Localization
Table 213. LiDAR Innovations in Advanced Robotics
Table 214. Computer Vision Advancements in Advanced Robotics
Table 215. Sensor Fusion Approaches in Advanced Robotics
Table 216. SAE Level 4-5 Regulations
Table 217. Testing and Certification Requirements
Table 218. Recent Regulatory Updates

List of Figures

Figure 1. Industrial Robotics Landscape
Figure 2. Global Market Size by Robot Type 2023-2046 (Million Units)
Figure 3. Global Market Size by Robot Type 2023-2046 (Million USD)
Figure 4. Historical progression of humanoid robots
Figure 5. Robotics Evolution Timeline
Figure 6. Service Robot in Japan
Figure 7. Technology Readiness Levels (TRL) for Advanced Robotics
Figure 8. Roadmap and Maturity Analysis by Industry
Figure 9. Robot swarms
Figure 10. System architecture of cloud robotics
Figure 11. Micro-bot
Figure 12. Robotics Technology Roadmap: Short-term Developments (2025-2030)
Figure 13. Robotics Technology Roadmap: Medium-term Developments (2030-2035)
Figure 14. Robotics Technology Roadmap: Long-term Developments (2035-2046)
Figure 15. EVE/NEO
Figure 16. RAISE-A1
Figure 17. Agibot product line-up
Figure 18. Digit humanoid robot
Figure 19. ANYbotics robot
Figure 20. Apptronick Apollo
Figure 21. Aubo Robotics - i series
Figure 22. Alex
Figure 23. BR002
Figure 24. Atlas
Figure 25. XR-4
Figure 26. Dreame Technology's second-generation bionic robot dog and general-purpose humanoid robot
Figure 27. Mercury X1
Figure 28. Prototype Ex-Robots humanoid robots
Figure 29. F&P Personal Robotics - P-Rob
Figure 30. Figure.ai humanoid robot
Figure 31. Figure 02 humanoid robot
Figure 32. GR-1
Figure 33. Sophia
Figure 34. Honda ASIMO
Figure 35. Kaleido
Figure 36. Forerunner
Figure 37. Keyper
Figure 38. KUKA - LBR iiwa series
Figure 39. Kuafu
Figure 40. CL-1
Figure 41. MagicHand S01
Figure 42. Monumental construction robot
Figure 43. Neura Robotics - Cognitive Cobots
Figure 44. Omron - TM5-700 and TM5X-700
Figure 45. Tora-One
Figure 46. HUBO2
Figure 47. XBot-L
Figure 48. Sanctuary AI Phoenix
Figure 49. Pepper Humanoid Robot
Figure 50. Astribot S1
Figure 51. Staubli - TX2touch series
Figure 52. Tesla Optimus Gen 2
Figure 53. Toyota T-HR3
Figure 54. UBTECH Walker
Figure 55. G1 foldable robot
Figure 56. WANDA
Figure 57. Unitree H1
Figure 58. CyberOne
Figure 59. PX5

The industrial robots market has undergone a dramatic transformation, evolving from simple, cage-enclosed machines into a sophisticated ecosystem encompassing traditional industrial robots, collaborative robots (cobots), humanoid robots, and intelligent mobile systems. This expanded landscape reflects manufacturing's shift toward flexible, adaptive automation that seamlessly integrates human workers with advanced robotic technologies across diverse industrial applications. Today's industrial robotics market spans multiple categories, each addressing specific manufacturing needs. Traditional industrial robots continue to dominate high-volume, high-precision applications like automotive welding and electronics assembly. However, collaborative robots have emerged as a game-changing segment, designed to work safely alongside human operators without protective barriers. These cobots feature advanced force-limiting technology, speed monitoring systems, and intuitive programming interfaces that enable rapid deployment and reconfiguration.

Humanoid robots represent the market's most ambitious frontier, offering human-like dexterity and mobility for complex manufacturing tasks. Companies like Boston Dynamics, Figure AI, and Agility Robotics are pioneering bipedal humanoid systems capable of navigating standard industrial environments, manipulating diverse objects, and performing multi-step assembly processes. These systems promise to address labor shortages while handling tasks too complex for traditional fixed-base robots.

Autonomous Mobile Robots (AMRs) and mobile manipulators combine mobility with manipulation capabilities, creating flexible automation solutions that can adapt to changing production layouts. These systems utilize advanced SLAM (Simultaneous Localization and Mapping) technology, LiDAR sensors, and AI-powered navigation to operate safely in dynamic environments alongside human workers.

Technological Convergence and AI Integration The integration of artificial intelligence has fundamentally transformed industrial robotics capabilities. Modern systems incorporate computer vision for real-time quality inspection, object recognition, and adaptive assembly. Machine learning algorithms enable robots to optimize their performance continuously, learning from production variations and improving accuracy over time. Multi-modal AI systems combine vision, force sensing, and audio processing to create robots capable of sophisticated decision-making.

Edge computing has become crucial for real-time processing, allowing robots to analyze sensor data locally and respond instantly to changing conditions. This capability is particularly important for collaborative applications where safety requires immediate response to human presence or unexpected obstacles. Advanced sensor fusion combines data from cameras, LiDAR, force sensors, and proximity detectors to create comprehensive environmental awareness.

The automotive industry remains the largest adopter of industrial robotics, increasingly deploying cobots for final assembly operations and humanoid robots for complex wiring and interior component installation. Electronics manufacturing has embraced collaborative robots for delicate component handling and testing procedures, while humanoid systems show promise for smartphone and tablet assembly requiring human-like dexterity. Food and beverage processing increasingly utilizes advanced robotics for packaging, quality inspection, and material handling. Collaborative robots excel in food preparation and packaging applications where flexibility and easy cleaning are essential. Pharmaceutical manufacturing adopts these technologies for sterile handling, precise dispensing, and complex assembly of medical devices.

Labor shortages continue driving market growth, with humanoid robots particularly positioned to address skilled labor gaps in industries like aerospace and shipbuilding. The aging workforce in developed nations creates opportunities for robots to perform physically demanding tasks while experienced workers focus on oversight and quality control.

Asia-Pacific leads global adoption, with China implementing ambitious automation initiatives across manufacturing sectors. Japanese companies like Honda and Toyota are pioneering humanoid robot applications in manufacturing, while South Korean firms focus on collaborative robotics for electronics production. European manufacturers emphasize collaborative systems and sustainable automation technologies, particularly in automotive and precision manufacturing. North American adoption focuses on advanced applications in aerospace, medical device manufacturing, and high-tech industries. The region's emphasis on reshoring manufacturing creates opportunities for sophisticated automation systems that can compete with low-cost overseas production.

The industrial robotics market is transitioning toward increasingly intelligent, adaptable systems. Robot-as-a-Service (RaaS) models are emerging to lower entry barriers, particularly for small and medium enterprises. These subscription-based approaches provide access to advanced robotics technology without significant capital investment.

Swarm robotics represents an emerging trend where multiple robots coordinate to accomplish complex tasks, particularly valuable in large-scale manufacturing and logistics operations. The integration of digital twin technology enables virtual testing and optimization of robotic systems before physical deployment.

As artificial intelligence continues advancing, the distinction between different robot types will blur, with systems becoming more versatile and capable of handling diverse tasks. The future industrial robotics market will likely feature increasingly autonomous systems that can adapt to new products, processes, and environments with minimal human intervention, fundamentally reshaping manufacturing's operational paradigms while creating new opportunities for human-robot collaboration.

"The Global Industrial Robots Market 2026-2046" provides in-depth analysis of the industrial robotics ecosystem, covering traditional industrial robots, collaborative robots (cobots), humanoid robots, autonomous mobile robots (AMRs), and emerging robotic technologies that are reshaping manufacturing across industries worldwide.

Report contents include:

Market Segmentation & Revenue Analysis:
- Detailed market size and growth forecasts for industrial robots, collaborative robots, humanoid robots, and mobile robots (2026-2046)
- Revenue projections by robot type, technology, component, and end-use industry
- Unit sales analysis across manufacturing, healthcare, logistics, agriculture, construction, and emerging sectors
- Regional market analysis covering North America, Europe, Japan, China, and India
- Pricing analysis and cost structure evaluation by robot category and application
Technology Landscape & Innovation Trends:
- Advanced AI integration including machine learning, computer vision, and sensor fusion technologies
- Collaborative robotics evolution through six stages of human-robot interaction
- Humanoid robot development for industrial applications with design considerations and manufacturing use cases
- Autonomous mobile robot navigation technologies and transition from AGVs to AMRs
- Robotic arms analysis including SCARA, Delta, and Cartesian robot configurations
- End-effector technologies and gripper systems for diverse manufacturing applications
Component Analysis & Supporting Systems:
- Comprehensive sensor and perception systems including cameras, LiDAR, radar, and thermal imaging
- AI and control systems featuring neuromorphic computing and edge processing capabilities
- Software and control platforms for robotics applications
- Linear motion systems, vision systems, and supporting infrastructure
- Advanced materials including metals, polymers, composites, smart materials, and nanomaterials
Industry Applications & End-Use Analysis:
- Automotive industry opportunities, challenges, and robotic applications
- Electronics manufacturing including 3C production challenges, quality control, and packaging automation
- Food and beverage industry requirements, product variety handling, and hygiene considerations
- Pharmaceutical manufacturing applications including sterile handling and precision dispensing
- Emerging industrial applications in additive manufacturing and flexible manufacturing systems
Emerging Technologies & Future Trends:
- Swarm robotics technologies and multi-robot coordination systems
- Human-robot collaboration advances and intuitive programming interfaces
- Self-learning and adaptive robots using reinforcement learning
- Cloud robotics and distributed computing architectures
- Digital twin integration for simulation, predictive maintenance, and performance optimization
- Robot-as-a-Service (RaaS) business models and subscription-based services
- Soft robotics materials and actuators for delicate handling applications
- Neuromorphic computing for energy-efficient robot perception
- Micro-nano robots for medical and industrial applications
- Brain-computer interfaces for advanced robot control
- Mobile collaborative robots combining mobility with manipulation
- Low-carbon robotics manufacturing and sustainable design approaches
Technical & Implementation Challenges:
- Perception and sensing limitations in complex environments
- Manipulation and dexterity requirements for human-like tasks
- Power and energy management optimization
- Human-robot interaction safety and regulatory compliance
- Integration complexity with existing manufacturing systems
- Skills gaps and workforce training requirements
Regulatory Landscape Analysis:
- Safety standards and requirements for collaborative robots
- Autonomous vehicle regulations and testing certifications
- Industrial robot safety regulations across major markets
- Data privacy and security requirements for connected robotics
- Regional regulatory differences and compliance considerations
Future Outlook & Technology Roadmap
Company Profiles & Competitive Landscape. Companies profiled include: 1X Technologies, ABB, Advanced Farm Technologies, Aethon, Agibot, Agility Robotics, Agilox, AheadForm, AIRSKIN, ANYbotics AG, Apptronik, Ati Motors, Aubo Robotics, Boardwalk Robotics, Booster Robotics, Boston Dynamics, BridgeDP Robotics, Bright Machines, Bruker Alicona, Clearpath Robotics, Clone Robotics, Cognibotics, Contoro Robotics, CynLr, Dataa Robotics, Denso, Devanthro, Dexterity Inc., Diligent Robotics, Dobot Robotics, Doosan Robotics, Elephant Robotics, Epson, Estun Automation, Eureka Robotics, F&P Personal Robotics, Fairino, Fanuc, FDROBOT, FESTO, Fetch Robotics, Figure AI, ForwardX, Fourier Intelligence, Franka Emika GmbH, fruitcore robotics GmbH, Furhat Robotics, Geekplus, GrayMatter Robotics, GreyOrange, H2 Clipper Inc., Haber, Han's Robot, Hanwha Robotics, HEBI Robotics, HIWIN, Holiday Robotics, Honda, Hyundai Robotics, Inceptio, Inivation AG, InVia Robotics, Inovance, Jaka Robotics, Kawasaki Heavy Industries, Kepler, Keybotic, Kivnon, KUKA, Leju Robotics, Libiao Robotics, LimX Dynamics, Locus Robotics, Macco Robotics, Magazino GmbH, MagicLab, Mbodi AI, Mecademic, MiR, Monumental, Mitsubishi Electric, NACHI, NAVIGANTIS, Neura Robotics GmbH, Nomagic, NVIDIA, Oinride Oy, Omron, OnRobot, Panasonic and more......

1. EXECUTIVE SUMMARY

1.1. Market Overview and Size
1.2. Robot Categorization
1.3. Industrial Robotics Landscape
1.4. Global Market Forecast
- 1.4.1. Units
- 1.4.2. Revenues
1.5. Key Drivers and Restraints
1.6. Technology Trends
- 1.6.1. Automation for improved efficiency
  - 1.6.1.1. Robot Density in Manufacturing 2020-2024
  - 1.6.1.2. Growth of Robot Users 2020-2024
- 1.6.2. Humanoid Robots
- 1.6.3. Collaborative Robots (Cobots)
- 1.6.4. Physical, Analytic and Generative AI
- 1.6.5. Robotics Evolution Timeline
- 1.6.6. Sustainability and Energy Consumption
- 1.6.7. Addressing Labor Shortages
- 1.6.8. Key Emerging Transitions in Sensing Technologies
1.7. Industry Convergence
- 1.7.1. Mobile Robots vs. Fixed Automation
- 1.7.2. Robot-as-a-Service (RaaS) Business Models
- 1.7.3. Industry 5.0 - Transformative Vision
- 1.7.4. Collaborative Robots Driving Industry 5.0
- 1.7.5. Parameter Comparison - Payload vs. Speed
1.8. Competitive Landscape
- 1.8.1. Global Competitive Landscape
- 1.8.2. Leading Companies by Robot Type
- 1.8.3. Major Industrial Robot Manufacturers
- 1.8.4. Service Robot Specialists
- 1.8.5. Cobot Manufacturers
- 1.8.6. AI Robotics Companies
- 1.8.7. Sensor and Component Developers
- 1.8.8. End-Effector Suppliers
- 1.8.9. Humanoid Robot Developers
1.9. Investment Trends
- 1.9.1. Historic Funding Trends
- 1.9.2. Recent investment
- 1.9.3. Venture Capital Funding of Robotics Startups

2. INTRODUCTION

2.1. Defining Advanced Robotics
- 2.1.1. Definitions of Key Terms
- 2.1.2. Classification of Robot Types
- 2.1.3. What are Robots?
  - 2.1.3.1. Industrial Robots
  - 2.1.3.2. Service Robots
  - 2.1.3.3. Collaborative Robots
  - 2.1.3.4. Mobile Robots
  - 2.1.3.5. Humanoid Robots
- 2.1.4. Why Robots?
  - 2.1.4.1. Productivity Enhancement
  - 2.1.4.2. Labor Shortage Solutions
  - 2.1.4.3. Safety Improvements
  - 2.1.4.4. Quality and Precision Requirements
2.2. Industrial Robots
2.3. Evolution from Traditional to Advanced Robotics
- 2.3.1. Historical Overview and Evolution
- 2.3.2. Current State of Robotics in 2025
- 2.3.3. Three Phases of Robot Adoption
- 2.3.4. Evolution from Industrial to Service Robots
2.4. Key Enabling Technologies
- 2.4.1. Artificial Intelligence and Machine Learning
  - 2.4.1.1. What is Artificial Intelligence?
    - 2.4.1.1.1. Key AI Methods for Robotics
  - 2.4.1.2. Deep Learning Approaches
  - 2.4.1.3. Convolutional Neural Networks in Robotics
- 2.4.2. Computer Vision
  - 2.4.2.1. Image Recognition Technologies
  - 2.4.2.2. Object Detection and Tracking
  - 2.4.2.3. Scene Understanding
- 2.4.3. Sensor Fusion
  - 2.4.3.1. Multi-sensor Integration
  - 2.4.3.2. Data Processing for Sensor Fusion
- 2.4.4. Advanced Materials
  - 2.4.4.1. Metals
  - 2.4.4.2. Plastics and Polymers
  - 2.4.4.3. Composites
  - 2.4.4.4. Elastomers
  - 2.4.4.5. Smart Materials
  - 2.4.4.6. Textiles
  - 2.4.4.7. Ceramics
  - 2.4.4.8. Biomaterials
  - 2.4.4.9. Nanomaterials
  - 2.4.4.10. Coatings
    - 2.4.4.10.1. Self-healing coatings
    - 2.4.4.10.2. Conductive coatings
  - 2.4.4.11. Flexible and Soft Materials
- 2.4.5. Edge Computing
  - 2.4.5.1. Local Processing vs. Cloud Computing
  - 2.4.5.2. Real-time Decision Making
- 2.4.6. SLAM - Simultaneous Localization and Mapping
  - 2.4.6.1. LiDAR SLAM
  - 2.4.6.2. Visual SLAM (vSLAM)
  - 2.4.6.3. Hybrid SLAM Approaches
- 2.4.7. Typical Sensors for Object Detection
  - 2.4.7.1. Camera-based Detection
  - 2.4.7.2. LiDAR-based Detection
  - 2.4.7.3. Radar Systems
  - 2.4.7.4. Ultrasonic Sensors
  - 2.4.7.5. Infrared and Thermal Sensors
2.5. Technology Readiness Assessment
- 2.5.1. Technology Readiness Levels (TRL)
- 2.5.2. Roadmap and Maturity Analysis by Industry
- 2.5.3. Readiness Level of Technologies by Application Sector
2.6. Standards and Regulations
- 2.6.1. Safety Requirements - Five Main Types
  - 2.6.1.1. Power and Force Limiting
  - 2.6.1.2. Speed and Separation Monitoring
  - 2.6.1.3. Hand Guiding
  - 2.6.1.4. Safety Monitored Stop
  - 2.6.1.5. Soft Impact Design
- 2.6.2. Regional Safety Standards
  - 2.6.2.1. European Standards
  - 2.6.2.2. Asian Standards
- 2.6.3. Global Regulatory Landscape
  - 2.6.3.1. Authorities Regulating Autonomous Driving
  - 2.6.3.2. Regulations for Delivery Robots and Drones
  - 2.6.3.3. Industrial Robot Regulations
  - 2.6.3.4. Data Privacy and Security Regulations
  - 2.6.3.5. Regional Differences in Regulations
  - 2.6.3.6. Data Security Requirements

3. GLOBAL MARKET ANALYSIS

3.1. Market Segmentation
- 3.1.1. By Robot Type
  - 3.1.1.1. Industrial Robots
    - 3.1.1.1.1. Units
    - 3.1.1.1.2. Revenues
  - 3.1.1.2. Collaborative Robots (Cobots)
    - 3.1.1.2.1. By revenues
    - 3.1.1.2.2. By Payload Capacity
    - 3.1.1.2.3. By Degrees of Freedom
    - 3.1.1.2.4. By End-Effector Type
  - 3.1.1.3. Humanoid Robots
    - 3.1.1.3.1. By Type (Full-Size, Medium, Small)
    - 3.1.1.3.2. By Application
  - 3.1.1.4. Mobile Robots
    - 3.1.1.4.1. Autonomous Mobile Robots (AMRs)
    - 3.1.1.4.2. Automated Guided Vehicles (AGVs)
    - 3.1.1.4.3. Grid-Based Automated Guided Carts (AGCs)
    - 3.1.1.4.4. Mobile Picking Robots
    - 3.1.1.4.5. Mobile Manipulators
    - 3.1.1.4.6. Last-Mile Delivery Robots
    - 3.1.1.4.7. Heavy-Duty L4 Autonomous Trucks
- 3.1.2. By Technology
  - 3.1.2.1. Navigation and Mapping
  - 3.1.2.2. Object Recognition and Tracking
  - 3.1.2.3. End-Effector and Manipulation
  - 3.1.2.4. Human-Robot Interaction
  - 3.1.2.5. Artificial Intelligence
- 3.1.3. By Component
  - 3.1.3.1. Hardware
    - 3.1.3.1.1. Sensors
    - 3.1.3.1.2. Actuators
    - 3.1.3.1.3. Power Systems
    - 3.1.3.1.4. Control Systems
    - 3.1.3.1.5. End-Effectors
  - 3.1.3.2. Software
    - 3.1.3.2.1. Control Software
    - 3.1.3.2.2. Perception Software
    - 3.1.3.2.3. Human-Machine Interface
  - 3.1.3.3. Services
    - 3.1.3.3.1. Installation and Integration
    - 3.1.3.3.2. Maintenance and Support
- 3.1.4. By End-use Industry
  - 3.1.4.1. Manufacturing
  - 3.1.4.2. Logistics and Warehousing
3.2. Regional Market Analysis
- 3.2.1. North America
- 3.2.2. Europe
- 3.2.3. Japan
- 3.2.4. China
- 3.2.5. India
3.3. Pricing Analysis and Cost Structure
- 3.3.1. Cost Analysis by Robot Type
  - 3.3.1.1. Industrial Robot Costs
  - 3.3.1.2. Collaborative Robot Costs
  - 3.3.1.3. Service Robot Costs
  - 3.3.1.4. Humanoid Robot Costs
  - 3.3.1.5. Mobile Robot Costs
- 3.3.2. Cost Analysis by Component
  - 3.3.2.1. Sensor Costs
  - 3.3.2.2. Actuator and Power System Costs
  - 3.3.2.3. Computing and Control System Costs
  - 3.3.2.4. End-Effector Costs
- 3.3.3. Payback Time/ROI by Application
  - 3.3.3.1. Manufacturing ROI
  - 3.3.3.2. Logistics ROI
- 3.3.4. Parameter Comparison - Payload vs. Max Traveling Speed
  - 3.3.4.1. Industrial Robots Performance Metrics
  - 3.3.4.2. Mobile Robots Performance Metrics
  - 3.3.4.3. Collaborative Robots Performance Metrics

4. TECHNOLOGY LANDSCAPE

4.1. Collaborative Robots (Cobots)
- 4.1.1. Six Stages of Human-Robot Interaction (HRI)
  - 4.1.1.1. Stage One: Non-Collaborative Robots
  - 4.1.1.2. Stage Two: Non-Collaborative with Virtual Guarding
  - 4.1.1.3. Stage Three: Laser Scanner Separation
  - 4.1.1.4. Stage Four: Shared Workspace
  - 4.1.1.5. Stage Five: Operators and Robots Working Together
  - 4.1.1.6. Stage Six: Autonomous Mobile Collaborative Robots
- 4.1.2. Traditional Industrial Robots vs. Collaborative Robots
- 4.1.3. Benefits and Drawbacks of Cobots
- 4.1.4. Safety Requirements for Cobots
  - 4.1.4.1. Power and Force Limiting
  - 4.1.4.2. Speed and Separation Monitoring
  - 4.1.4.3. Hand Guiding
  - 4.1.4.4. Safety-Rated Monitored Stop
  - 4.1.4.5. Biomechanical Limit Criteria
- 4.1.5. Cobot Cost Analysis
- 4.1.6. Payload Summary of Cobots
- 4.1.7. Overview of Commercialized Cobots
  - 4.1.7.1. Benchmarking Based on DoF, Payload, Weight
  - 4.1.7.2. 6-DoF Cobots
  - 4.1.7.3. 7-DoF Cobots
  - 4.1.7.4. Price Categories of Cobots
- 4.1.8. Market Players
4.2. Autonomous Mobile Robots (AMRs)
- 4.2.1. Transition from AGVs to AMRs
- 4.2.2. Technology Evolution Towards Fully Autonomous Mobile Robots
- 4.2.3. AMR Navigation Technologies
4.3. Humanoid Industrial Robots
- 4.3.1. Applications in Manufacturing
- 4.3.2. Design Considerations
- 4.3.3. Market Players
4.4. Mobile Robots
- 4.4.1. Rolling Robots
- 4.4.2. Market Players
4.5. Robotic Arms
- 4.5.1. Types and Applications
- 4.5.2. SCARA Robots
- 4.5.3. Delta Robots
- 4.5.4. Cartesian (Gantry) Robots
- 4.5.5. Market Players
4.6. Robotic Grippers
- 4.6.1. Market Players
4.7. Software & Control
4.8. Supporting Systems
- 4.8.1. Linear Motion Systems
  - 4.8.1.1. Rails
  - 4.8.1.2. Actuators for Cartesian robots or auxiliary axes
  - 4.8.1.3. Market Players
- 4.8.2. Vision Systems
  - 4.8.2.1. Cameras
  - 4.8.2.2. LiDAR
  - 4.8.2.3. Sensors for guidance/QC
  - 4.8.2.4. Market Players

5. TECHNOLOGY COMPONENTS AND SUBSYSTEMS

5.1. AI and Control Systems
- 5.1.1. Artificial Intelligence and Machine Learning
  - 5.1.1.1. AI Applications in Robotics
  - 5.1.1.2. Machine Learning Techniques for Robotics
- 5.1.2. End-to-end AI
  - 5.1.2.1. Perception to Action Systems
  - 5.1.2.2. Implementation Challenges
- 5.1.3. Multi-modal AI Algorithms
  - 5.1.3.1. Vision-Language Models
  - 5.1.3.2. Sensor-Fusion AI
- 5.1.4. Intelligent Control Systems and Optimization
  - 5.1.4.1. Control Architectures
  - 5.1.4.2. Motion Planning
5.2. Sensors and Perception
- 5.2.1. Sensory Systems in Robots
  - 5.2.1.1. Importance of Sensing in Robots
  - 5.2.1.2. Typical Sensors Used for Robots
- 5.2.2. Sensors by Functions and Tasks
  - 5.2.2.1. Navigation and Mapping
  - 5.2.2.2. Object Detection and Recognition
  - 5.2.2.3. Safety and Collision Avoidance
  - 5.2.2.4. Environmental Sensing
- 5.2.3. Sensors by Robot Type
  - 5.2.3.1. Industrial Robotic Arms
  - 5.2.3.2. AGVs and AMRs
  - 5.2.3.3. Collaborative Robots
  - 5.2.3.4. Drones
  - 5.2.3.5. Service Robots
  - 5.2.3.6. Underwater Robots
  - 5.2.3.7. Agricultural Robots
  - 5.2.3.8. Cleaning Robots
  - 5.2.3.9. Social Robots
- 5.2.4. Vision Systems
  - 5.2.4.1. Cameras (RGB, Depth, Thermal, Event-based)
    - 5.2.4.1.1. RGB/Visible Light Cameras
    - 5.2.4.1.2. Depth Cameras
    - 5.2.4.1.3. Thermal Cameras
    - 5.2.4.1.4. Event-based Cameras
  - 5.2.4.2. CMOS Image Sensors vs. CCD Cameras
    - 5.2.4.2.1. Comparative Analysis
  - 5.2.4.3. Stereo Vision and 3D Perception
    - 5.2.4.3.1. Depth Calculation Methods
    - 5.2.4.3.2. 3D Reconstruction
  - 5.2.4.4. In-Camera Computer Vision
    - 5.2.4.4.1. Edge Processing
    - 5.2.4.4.2. Applications in Autonomous Vehicles
  - 5.2.4.5. Hyperspectral Imaging Sensors

6. END-USE INDUSTRY ANALYSIS

6.1. Automotive
- 6.1.1. Opportunities and Challenges
- 6.1.2. Applications
6.2. Electronics
- 6.2.1. 3C Manufacturing Challenges
- 6.2.2. Production Volume Requirements
- 6.2.3. Quality Control
- 6.2.4. Applications
- 6.2.5. Testing and Inspection
- 6.2.6. Packaging
6.3. Food and Beverage
- 6.3.1. Industry Challenges and Requirements
- 6.3.2. Product Variety
- 6.3.3. Applications
  - 6.3.3.1. Palletizing
  - 6.3.3.2. Packaging
  - 6.3.3.3. Food Processing
6.4. Pharmaceutical
- 6.4.1. Industry Requirements
- 6.4.2. Applications
6.5. Emerging Industrial Applications
- 6.5.1. Additive manufacturing integration
- 6.5.2. Flexible manufacturing systems
- 6.5.3. Lights-out manufacturing
- 6.5.4. Mass customization robotics

7. MARKET DRIVERS AND RESTRAINTS

7.1. Market Drivers
- 7.1.1. Labor Shortages and Wage Inflation
  - 7.1.1.1. Global Labor Market Trends
  - 7.1.1.2. Industry-Specific Impacts
- 7.1.2. Productivity and Efficiency Demands
  - 7.1.2.1. Manufacturing Efficiency
  - 7.1.2.2. Logistics Optimization
  - 7.1.2.3. Healthcare Productivity
- 7.1.3. Quality and Precision Requirements
  - 7.1.3.1. Manufacturing Quality Control
  - 7.1.3.2. Healthcare Precision
- 7.1.4. Workplace Safety Concerns
  - 7.1.4.1. Hazardous Environment Applications
  - 7.1.4.2. Ergonomic Considerations
- 7.1.5. Aging Population
  - 7.1.5.1. Healthcare Applications
  - 7.1.5.2. Workforce Replacement
- 7.1.6. Advancements in Artificial Intelligence and Machine Learning
  - 7.1.6.1. Improved Perception Systems
  - 7.1.6.2. Enhanced Decision Making
  - 7.1.6.3. Autonomous Capabilities
- 7.1.7. Need for Personal Assistance and Companionship
  - 7.1.7.1. Eldercare Applications
  - 7.1.7.2. Household Assistance
- 7.1.8. Exploration of Hazardous and Extreme Environments
  - 7.1.8.1. Nuclear Applications
  - 7.1.8.2. Deep Sea Exploration
  - 7.1.8.3. Space Applications
- 7.1.9. E-commerce Growth
  - 7.1.9.1. Last-Mile Delivery Challenges
  - 7.1.9.2. Warehouse Automation Needs
7.2. Market Restraints
- 7.2.1. High Initial Investment Costs
  - 7.2.1.1. Robot Hardware Costs
  - 7.2.1.2. Integration and Implementation Costs
- 7.2.2. Technical Limitations
  - 7.2.2.1. AI and Perception Challenges
  - 7.2.2.2. Manipulation Challenges
  - 7.2.2.3. Energy and Power Limitations
- 7.2.3. Implementation Challenges
  - 7.2.3.1. Integration with Existing Systems
  - 7.2.3.2. User Training and Adoption
- 7.2.4. Safety and Regulatory Concerns
  - 7.2.4.1. Human-Robot Collaboration Safety
  - 7.2.4.2. Autonomous System Regulations
- 7.2.5. Workforce Resistance and Social Acceptance
  - 7.2.5.1. Employment Concerns
  - 7.2.5.2. Human-Robot Interaction Challenges

8. EMERGING TRENDS AND DEVELOPMENTS

8.1. Swarm Robotics
- 8.1.1. Technologies and Approaches
- 8.1.2. Application Potential
- 8.1.3. Market Outlook
8.2. Human-Robot Collaboration
- 8.2.1. Advances in Safe Interaction
- 8.2.2. Intuitive Programming Interfaces
- 8.2.3. Market Implementation Examples
8.3. Self-Learning and Adaptive Robots
- 8.3.1. Reinforcement Learning Applications
- 8.3.2. Transfer Learning
- 8.3.3. Continual Learning Systems
8.4. Cloud Robotics
- 8.4.1. Distributed Computing for Robotics
- 8.4.2. Remote Operation Capabilities
8.5. Digital Twin Integration
- 8.5.1. Simulation and Planning
- 8.5.2. Predictive Maintenance
- 8.5.3. Performance Optimization
8.6. Robot-as-a-Service (RaaS) Business Models
- 8.6.1. Subscription-Based Services
- 8.6.2. Pay-Per-Use Models
- 8.6.3. Market Adoption Trends
8.7. Soft Robotics
- 8.7.1. Materials and Actuators
8.8. Neuromorphic Computing for Robotics
- 8.8.1. Brain-Inspired Computing Architectures
- 8.8.2. Applications in Perception
- 8.8.3. Energy Efficiency Benefits
8.9. Micro-nano Robots
- 8.9.1. Technologies and Designs
- 8.9.2. Medical Applications
- 8.9.3. Industrial Applications
8.10. Brain Computer Interfaces
- 8.10.1. Non-Invasive BCIs
- 8.10.2. Invasive BCIs
- 8.10.3. Applications in Robot Control
8.11. Mobile Cobots
- 8.11.1. Technologies and Designs
- 8.11.2. Applications
- 8.11.3. Market Outlook
8.12. Industry 5.0 and Collaborative Robots
- 8.12.1. Human-Machine Collaboration
- 8.12.2. Sustainable Manufacturing
- 8.12.3. Implementation Examples
8.13. Low-carbon Robotics Manufacturing
- 8.13.1. Sustainable Design Approaches
- 8.13.2. Energy-Efficient Operation
- 8.13.3. End-of-Life Considerations
8.14. Autonomous Navigation and Localization
- 8.14.1. SLAM Advancements
- 8.14.2. Multi-Sensor Fusion
- 8.14.3. GPS-Denied Navigation
8.15. Navigation Sensors Driven by Autonomous Mobility
- 8.15.1. LiDAR Innovations
- 8.15.2. Computer Vision Advancements
- 8.15.3. Sensor Fusion Approaches

9. CHALLENGES AND OPPORTUNITIES

9.1. Technical Challenges
- 9.1.1. Perception and Sensing
- 9.1.2. Manipulation and Dexterity
- 9.1.3. Power and Energy Management
- 9.1.4. Human-Robot Interaction
9.2. Market Challenges
- 9.2.1. Cost Barriers
- 9.2.2. Skills and Training Gaps
- 9.2.3. Integration Complexity
- 9.2.4. Supply Chain Issues
9.3. Regulatory Challenges
- 9.3.1. Regulations for Autonomous Vehicles
  - 9.3.1.1. SAE Level 4-5 Regulations
  - 9.3.1.2. Testing and Certification Requirements
- 9.3.2. Regulations for Delivery Drones
  - 9.3.2.1. Airspace Regulations
  - 9.3.2.2. Payload and Distance Limitations
- 9.3.3. Recent Regulatory Updates

10. FUTURE OUTLOOK

10.1. Technology Roadmap (2025-2046)
- 10.1.1. Short-term Developments (2025-2030)
- 10.1.2. Medium-term Developments (2030-2035)
- 10.1.3. Long-term Developments (2035-2046)
10.2. Industry Convergence Opportunities
- 10.2.1. Robotics and AI
- 10.2.2. Robotics and IoT
- 10.2.3. Robotics and Advanced Manufacturing
10.3. Robotics and the Future of Work
- 10.3.1. Job Transformation
- 10.3.2. New Skill Requirements
- 10.3.3. Human-Robot Collaboration Models

産業用ロボットの世界市場（2026年～2046年）

The Global Industrial Robots Market 2026-2046

目次

第1章エグゼクティブサマリー

第2章イントロダクション

第3章世界市場の分析

第4章技術の情勢

第5章技術コンポーネントとサブシステム

第6章最終用途産業の分析

第7章市場促進要因と抑制要因

第8章新たな動向と発展

第9章課題と機会

第10章将来の見通し

第11章企業プロファイル（企業120社のプロファイル）

第12章参考文献

List of Tables

List of Figures

Report contents include:

TABLE OF CONTENTS

1. EXECUTIVE SUMMARY

2. INTRODUCTION

3. GLOBAL MARKET ANALYSIS

4. TECHNOLOGY LANDSCAPE

5. TECHNOLOGY COMPONENTS AND SUBSYSTEMS

6. END-USE INDUSTRY ANALYSIS

7. MARKET DRIVERS AND RESTRAINTS

8. EMERGING TRENDS AND DEVELOPMENTS

9. CHALLENGES AND OPPORTUNITIES

10. FUTURE OUTLOOK

11. COMPANY PROFILES (120 company profiles)

12. REFERENCES

産業用ロボットの世界市場（2026年～2046年）

The Global Industrial Robots Market 2026-2046

目次

第1章 エグゼクティブサマリー

第2章 イントロダクション

第3章 世界市場の分析

第4章 技術の情勢

第5章 技術コンポーネントとサブシステム

第6章 最終用途産業の分析

第7章 市場促進要因と抑制要因

第8章 新たな動向と発展

第9章 課題と機会

第10章 将来の見通し

第11章 企業プロファイル（企業120社のプロファイル）

第12章 参考文献

List of Tables

List of Figures

Report contents include:

TABLE OF CONTENTS

1. EXECUTIVE SUMMARY

2. INTRODUCTION

3. GLOBAL MARKET ANALYSIS

4. TECHNOLOGY LANDSCAPE

5. TECHNOLOGY COMPONENTS AND SUBSYSTEMS

6. END-USE INDUSTRY ANALYSIS

7. MARKET DRIVERS AND RESTRAINTS

8. EMERGING TRENDS AND DEVELOPMENTS

9. CHALLENGES AND OPPORTUNITIES

10. FUTURE OUTLOOK

11. COMPANY PROFILES (120 company profiles)

12. REFERENCES

第1章エグゼクティブサマリー

第2章イントロダクション

第3章世界市場の分析

第4章技術の情勢

第5章技術コンポーネントとサブシステム

第6章最終用途産業の分析

第7章市場促進要因と抑制要因

第8章新たな動向と発展

第9章課題と機会

第10章将来の見通し

第11章企業プロファイル（企業120社のプロファイル）

第12章参考文献