全球新興機器人市場（2027-2037 年）

新興機器人是指打破傳統工業機器人基本假設的一類機器。具體而言，它們在籠子之外、非結構化環境中運行，與人類協同工作，或在缺乏可靠通訊鏈路的場所運行，因此依賴於感知、學習和機載決策，而非受控單元內預先設定的路徑。新興機器人是全球自動化經濟中成長最快、最容易被誤解的領域。該市場涵蓋七大垂直領域：倉儲物流、國防、人形機器人、製造與自動化、建築與基礎設施、航太以及機器人平台模型。未來十年將有三個結構性事實定義著新興機器人的發展方向，而這三個事實都與目前普遍接受的傳統觀點相違背。

首先，根本不存在所謂的通用機器人。目前全球所有商業部署的系統，要么是為特定任務預先編寫的腳本，要么是遠端控制的，要么是在監督下運行的。地球上部署的人形機器人總數——包括比亞迪、GXO、亞馬遜、寶馬和賓士——加起來也只有幾百個。雖然機器人數量確實在成長，但通用自主性尚未實現。而最接近真正任務級自主性的領域並非人形機器人，而是國防領域。在國防領域，我們必須在GPS和通訊中斷的情況下解決問題，而不是拖延。

其次，價值並非存在於資本流入之處。驅動裝置——包括執行器和靈巧的機械手（它們本身也是執行器組件）——佔據了人形機器人絕大部分的零件成本。半導體所佔比例很小且還在不斷縮小，即使是安裝在機器人中的矽晶片，也主要用於馬達控制，而非人工智慧運算。中國供應商在構成機器人的主要機械部件方面擁有決定性的結構性成本優勢。這得益於其國內端到端的供應鏈以及對稀土元素磁體的近乎絕對的壟斷。西方基於控制智慧層的戰略，實際上只是基於控制機器人最小部件的戰略。

第三，限制因素並非演算法，而是物理因素。機器人脫離電源和網路連接後能做什麼，取決於的不是模型的質量，而是功耗、記憶體和頻寬。一個完整的運行堆疊所需的記憶體超過了板載加速器所能提供的容量，而用於推理的1瓦功率就意味著用於運行的1瓦功率減少。由此產生的運行運算和記憶層是組件市場中成長最快的領域，但目前還沒有佔據主導地位的廠商，也沒有出現在任何已發布的市場地圖中。

這一組件層才是機器成本的真正核心，也是產業中資金投入最少的部分。這種不平衡正是本報告的核心投資洞見。

《新興機器人全球市場（2027-2037）》報告全面分析了七個重塑物理自動化格局的產業特定市場、其三級層級構造以及相關投資。該報告由Future Markets, Inc.出版，將至2037年的全面定量預測與對這些機器當前能力的坦誠評估相結合。報告引入了“自主性依賴等級（A0-A4）”，這一分類標準統一應用於所有報告分析的公司，區分了設計能力和實際運行中觀察到的等級。該報告首次在同類市場研究中揭示，目前尚無任何商業部署的系統達到A4等級；市場上自主性最高的系統並非人形機器人，而是國防領域；供應商宣稱的能力與實際性能之間的差距，恰恰在資本最為集中的領域最為顯著。

一份詳盡的材料清單(BOM) 分析澄清了該領域長期以來備受爭議的「價值歸屬」問題。報告顯示，動力系統佔人形機器人成本的 73%，半導體成本佔比從 8% 降至 5%。成本佔有率、利潤率和保持競爭力是三個不同的因素，其中中國在最關鍵的幾個類別中擁有 40% 至 60% 的成本優勢。該預測涵蓋 2027 年至 2037 年的七個垂直市場、七個組件類別、五種經營模式和五個地區，並分別在基準情境、保守情境和樂觀情境下進行了分析。此外，一項全面的敏感度分析表明，消費級人形機器人的價格閾值是影響市場的最大因素。

目錄：

• 執行摘要－主要發現、三大結構性問題及2026年以後的變化
• 引言與分類－新興機器人技術的定義、市場概況與三層層級構造（組件→平台→智慧）
• 自主性差距－自主性依賴程度（A0-A4）；產業設計的自主性與實際測量的自主性；資料缺失所帶來的問題；國防領域領先的原因
• 價值取得與材料清單(BOM) - 完整的物料清單分解；驅動零件佔有率；半導體零件佔有率；成本佔有率、利潤率與國防；中國成本優勢的量化
• 供應鍊及零件－執行器和傳動裝置；精密機械手（詳細分析：6.29億美元→199億美元，複合年成長率41.3%）；感測器；電源系統；邊緣半導體；稀土元素和電池集中化；運算計算和記憶體
• 機器人平台模型 - 通用模型市場；垂直整合的壓力；數據問題；該細分市場價值佔有率下降的原因。
• 人形機器人－三階段擴散模式；出貨量與平均售價（ASP）比較；實際部署條件檢驗；市場集中度及向中國的轉移
• 倉儲物流－細分領域；揀貨速度的限制；每次揀貨成本；向機器人即服務 (RaaS) 的轉型；為什麼人形機器人在這裡處於劣勢
• 製造與自動化－單位成本結構；批量經濟；熟練工人短缺；程式設計成本曲線
• 國防領域－消耗性部隊；烏克蘭設計自主性和作戰自主性的比較；電力預算；無人機系統對抗措施的經濟性；自主性許可
• 太空——光速延遲和遠端操作的崩壞；抗輻射加固計算的差距；在軌道維護、ISAM 和太空碎片清除。
• 建築與基礎設施——50年的生產力差距；自動化前沿；為什麼太陽能將成為“楔子”
• 2027-2037年市場預測－依產業、組件、經營模式、地區及銷售分類；三種情境；敏感度分析；重複累計做法
• 投資與競爭格局－創業投資（VC）趨勢；資本配置與商機；各組成部分面臨資金短缺困境；退出環境
• 公司簡介 - 168 家具有自主權的公司簡介。本次專題報導的公司包括：1X Technologies、ABB、Agibot、Agile Robots、Agility Robotics、AheadForm、AIRSKIN、AI2Robotics (AI2)、AmbiRobotics、Anduril Industries、ANYbotics、Apptronik、ARX Robotics、Aubo Robotics、Anduril Industries、ANYbotics、Apptronik、ARX Robotics、Aubo Robotics、Augmentus、百度數、北京研發中心(Brittics)、Augmentus、Augmentus） Robotics、Boston Dynamics、BridgeDP Robotics、Bright Machines、BRINC、Built Robotics、BXI Robotics、Charge Robotics、ClearPath Robotics、ClearSpace、Clone Robotics、Cognibotics、Contoro Robotics、Cosmic Robotics、Covarone Robotics、Covarnibotics、Deepotics、Deepvaro、Deepvaro、DeepAtics、Deep AI、Dexory、Dexterity、Diligent Robotics、Dobot Robotics、Doosan Robotics、dRobotics、Dusty Robotics、Dyna Robotics、Electron Robots 和 Elephant。 Robotics、EngineAI、Epoch Robotics、Eureka Robotics、EX Robots、Exotec、Fanuc、FBR (Hadrian X)、FDROBOT、FESTO、Field AI、Figure AI、Fluid Wire Robotics、Formant、Forterra、ForwardX、Figure AI、Fluid。 Robotics、GITAI、GrayMatter Robotics、Hadrian、HavocAI、HEBI Robotics、Honda、Humanoid、Hypercraft、Icarus Robotics、Invation、IntBot、intuiCell、Jacobi Robotics 等。

目錄

第1章執行摘要

第2章 引言：定義、分類與新型機器人技術棧

第3章：自主性差距：為什麼通用機器人不存在

• 當前通用能力狀況
• 「自主的」的四種意義
• 遠端操作作為數據供應
• 自主性依賴分類
• 基礎設施依賴性問題
• 反駁論點
• 對預測的影響

第4章：價值取得：材料清單清單經濟學

• 衝突
• 材料清單實際顯示的內容
• 雙方通用的錯誤
• 真正可以防守的陣地在哪裡？

第5章 供應鏈與組件層

• 市場地圖中省略的圖層
• 執行器、諧波驅動器、變速器
• 末端執行器和靈巧的雙手
• 感測器和感知
• 電力系統和運作能量
• 半導體和邊緣運算
• 操作記憶和檢驗的自主性
• 地理集中度和瓶頸

第6章：基本模型與機器人學習

• Layer及其雄心
• 數據問題
• 垂直整合的壓力
• 推理約束
• 競爭格局

第7章 人形生物

• 市場概覽
• 部署的實際情況
• 3波結構
• 能力差距
• 競爭結構

第8章：倉儲與物流

• 市場概覽
• 任務腳本限制，以及為什麼在這裡這不是問題。
• 經濟效益：每次採摘成本
• 買家實際購買的商品
• 經營模式：向 RaaS 轉型
• 競爭格局

第9章 製造與自動化

• 市場概覽
• 機器人的真正成本並非機器人本身。
• 批次大小視窗
• 勞動力限制是特定情況下的，而不是普遍存在的。
• 競爭格局

第10章 空間機器人學

• 市場概覽
• 為什麼宇宙不能欺騙
• 抗輻射加固計算差距
• 自主性的現實
• 競爭格局

第11章 建築與基礎設施

• 市場概覽
• 抵制施工的原因
• 自動化的前沿
• 競爭格局

第12章 國防與安全

• 市場概覽
• 採購逆轉
• 設計自主性和觀察到的自主性之間的差距
• 領域
• 公司簡介

第13章：公司簡介（168家公司簡介）

第14章參考文獻

Emerging robotics comprises the classes of machine that break the founding assumptions of classical industrial robotics - operating outside cages, in unstructured environments, alongside people, or beyond the reach of a reliable communications link - and that consequently depend on perception, learning and onboard decision-making rather than on a pre-programmed path in a controlled cell. Emerging robotics is the fastest-growing segment of the global automation economy and the most widely misunderstood. The market spans seven verticals: warehouse and logistics, defence, humanoids, manufacturing and automation, construction and infrastructure, space, and robotics foundation models. Three structural facts define the decade ahead, and each cuts against the prevailing narrative.

The first is that no general-purpose robot exists. Every commercially deployed system in the world today is task-scripted, teleoperated, or supervised. The most-cited humanoid deployments on earth - at BYD, GXO, Amazon, BMW and Mercedes - amount, in total, to a few hundred machines. The growth is real; general autonomy is not. And the systems operating closest to genuine mission-level autonomy are found not in humanoids but in defence, where GPS-denied and communications-denied conditions have forced the problem to be solved rather than deferred.

The second is that value does not sit where capital is flowing. Actuation - actuators together with dexterous hands, which are themselves actuator assemblies - constitutes the overwhelming majority of a humanoid robot's bill of materials. Semiconductors are a small and shrinking fraction of it, and even the silicon aboard the machine is majority motor-control rather than AI compute. Chinese suppliers hold a decisive structural cost advantage in precisely the mechanical categories that dominate the machine, arising from end-to-end domestic supply chains and near-total control of rare-earth magnets. A Western strategy predicated on owning the intelligence layer is a strategy predicated on owning the smallest part of the robot.

The third is that the binding constraint is physical, not algorithmic. Power, memory and bandwidth - not model quality - determine what a robot can do away from a wall socket and a network connection. A full manipulation stack demands more memory than onboard accelerators can supply, and every watt spent on inference is a watt not spent on motion. The operational compute and memory layer that follows from this is the fastest-growing category in the components market, it has no incumbent, and it appears on no published market map.

The components layer is where the machine's cost actually lives, and it is the least funded part of the industry. That asymmetry is the central investment finding of this report.

The Global Emerging Robotics Market 2027–2037 is a comprehensive analysis of the seven verticals reshaping physical automation, the three-layer stack beneath them, and the capital being deployed against both. Published by Future Markets, Inc., the report combines a full quantitative forecast to 2037 with an unusually direct assessment of what these machines can and cannot presently do. The report introduces the Autonomy Dependency Scale (A0–A4), a classification applied consistently to every company profiled, distinguishing designed capability from observed operating class. It records, for the first time in a market study of this kind, that nothing in commercial deployment operates at A4, that the most autonomous systems on the market are in defence rather than humanoids, and that the gap between vendor claims and field performance is widest precisely where capital is most concentrated.

A detailed bill-of-materials analysis resolves the value-capture dispute that has dominated the sector's commentary. The report demonstrates that actuation accounts for 73% of a humanoid's cost, that semiconductors fall from 8% to 5%, and that cost share, margin and defensibility are three different things - with a 40–60% Chinese cost advantage in the categories that matter most. The forecast covers 2027–2037 across seven verticals, seven component categories, five business models and five regions, in base, conservative and optimistic scenarios, with a full sensitivity analysis identifying the consumer humanoid price threshold as the single largest variable in the market.

Contents:

• Executive summary - key findings, the three structural claims, and what changed since 2026
• Introduction and taxonomy - defining emerging robotics; the market map; the three-layer stack (components → platforms → intelligence)
• The autonomy gap - the Autonomy Dependency Scale A0–A4; designed versus observed autonomy by vertical; the data scarcity problem; why defence leads
• Value capture and the bill of materials - full BOM decomposition; the actuation share; the semiconductor share; cost share versus margin versus defensibility; the Chinese cost advantage quantified
• Supply chain and components - actuators and transmissions; dexterous hands (deep dive: $629M → $19.9bn, 41.3% CAGR); sensors; power systems; edge silicon; rare-earth and battery concentration; operational compute and memory
• Robotics foundation models - the merchant model market; the vertical-integration squeeze; the data problem; why the layer's share of value declines
• Humanoids - the three-wave adoption model; shipments versus ASP; the deployment reality check; concentration and the relocation of the market to China
• Warehouse and logistics - sub-segments; the pick-rate frontier; cost per pick; the RaaS transition; why the humanoid loses here
• Manufacturing and automation - the cell cost stack; batch-size economics; the skilled-trade shortage; the programming-cost curve
• Defence - attritable mass; designed versus observed autonomy in Ukraine; the power budget; counter-UAS economics; autonomy licensing
• Space - light-time delay and the collapse of teleoperation; the radiation-hardened compute gap; on-orbit servicing, ISAM and debris removal
• Construction and infrastructure - the fifty-year productivity divergence; the automation frontier; why solar is the wedge
• Market forecasts 2027–2037 - by vertical, component, business model, region and units; three scenarios; sensitivity analysis; the double-counting convention
• Investment and competitive landscape - VC trajectory; capital allocation versus revenue opportunity; the starved components layer; exit environment
• Company profiles - 168 companies with autonomy classification. Companies Profiled include 1X Technologies, ABB, Agibot, Agile Robots, Agility Robotics, AheadForm, AIRSKIN, AI² Robotics (AI2), AmbiRobotics, Anduril Industries, ANYbotics, Apptronik, ARX Robotics, Aubo Robotics, Augmentus, Baidu, BHRIC (Beijing Humanoid Robot Innovation Center), Boardwalk Robotics, Boost Robotics, Booster Robotics, Boston Dynamics, BridgeDP Robotics, Bright Machines, BRINC, Built Robotics, BXI Robotics, Charge Robotics, ClearPath Robotics, ClearSpace, Clone Robotics, Cognibotics, Contoro Robotics, Cosmic Robotics, Covariant, Daimon Robotics, Dataa Robotics, Deep Robotics, DeepCloud AI, Dexory, Dexterity, Diligent Robotics, Dobot Robotics, Doosan Robotics, dRobotics, Dusty Robotics, Dyna Robotics, Electron Robots, Elephant Robotics, EngineAI, Epoch Robotics, Eureka Robotics, EX Robots, Exotec, Fanuc, FBR (Hadrian X), FDROBOT, FESTO, Field AI, Figure AI, Fluid Wire Robotics, Formant, Forterra, ForwardX, Foundation, Fourier Intelligence, Franka Emika, Galaxea AI, Galbot, Gecko Robotics, Ghost Robotics, GITAI, GrayMatter Robotics, Hadrian, HavocAI, HEBI Robotics, Honda, Humanoid, Hypercraft, Icarus Robotics, Inivation, IntBot, intuiCell, Jacobi Robotics and more....

Table of Contents

1 EXECUTIVE SUMMARY

• 1.1 The Market in Summary
• 1.2 Principal Findings
  • 1.2.1 No General-Purpose Robot Exists, and None Is Close
  • 1.2.2 The Most Autonomous Systems on the Market Map Are in Defence, Not in Humanoids
  • 1.2.3 Is Value Concentrated in Actuation, and is the Concentration Structural
  • 1.2.4 The Binding Constraint Is Physical, Not Algorithmic
• 1.3 Market Forecast Summary
• 1.4 Implications for Positioning

2 INTRODUCTION: MARKET DEFINITION, TAXONOMY AND THE EMERGING ROBOTICS STACK

• 2.1 Defining Emerging Robotics
• 2.2 The Commercial Consequence of the Definition
  • 2.2.1 The Five Competing Business Models
• 2.3 The Seven-Vertical Taxonomy
  • 2.3.1 Foundation Models as a Layer Rather Than a Vertical
  • 2.3.2 Humanoids as a Form Factor Rather Than a Market
  • 2.3.3 The Growing Primacy of Defence
• 2.4 The Emerging Robotics Stack
  • 2.4.1 The Operational Compute and Memory Layer
  • 2.4.2 The Physical Components Layer
• 2.5 Scope Exclusions
• 2.6 Methodology and Basis of Estimates
  • 2.6.1 The Treatment of Pilots
  • 2.6.2 The Treatment of Teleoperated Systems
  • 2.6.3 The Treatment of Replacement Demand

3 THE AUTONOMY GAP: WHY NO GENERAL-PURPOSE ROBOT EXISTS

• 3.1 The Present State of General-Purpose Capability
• 3.2 The Four Senses of "Autonomous"
  • 3.2.1 The Consequence of Definitional Slippage
• 3.3 Teleoperation as Data Supply
  • 3.3.1 Teleoperation Within the Cost of Goods Sold
  • 3.3.2 The Economics of the Pilot
  • 3.3.3 The Step Function
• 3.4 The Autonomy Dependency Classification
  • 3.4.1 Application Across the Market Map
  • 3.4.2 The Primacy of Defence in Demonstrated Autonomy
  • 3.4.3 The Constraint Is Not Model Quality
• 3.5 The Infrastructure Dependency Problem
  • 3.5.1 Availability
  • 3.5.2 The Onboard Memory Wall
  • 3.5.3 Accountability and Operational Memory
• 3.6 The Counter-Argument
  • 3.6.1 Improving Connectivity
  • 3.6.2 The Trajectory of Onboard Silicon
  • 3.6.3 An Institutional Answer to Accountability
  • 3.6.4 Assessment
• 3.7 Consequences for the Forecast
  • 3.7.1 Humanoids
  • 3.7.2 Defence
  • 3.7.3 Foundation Models

4 VALUE CAPTURE: BILL-OF-MATERIALS ECONOMICS

• 4.1 The Dispute
• 4.2 What the Bill of Materials Actually Shows
  • 4.2.1 The Mechanical Dominance of Cost
  • 4.2.2 The Concentration Is Structural, Not Transitional
  • 4.2.3 Even the Silicon Is Mostly Actuation
• 4.3 The Error Common to Both Camps
  • 4.3.1 Cost Share Is Not Margin Capture
  • 4.3.2 Margin Capture Is Not Defensibility
• 4.4 Where the Defensible Positions Actually Lie
  • 4.4.1 High-Performance Actuation, Not Actuation
  • 4.4.2 Operational Compute and Memory
  • 4.4.3 Integration, Which Nobody Is Arguing For

5 THE SUPPLY CHAIN AND COMPONENTS LAYER

• 5.1 The Layer the Market Map Omits
• 5.2 Actuators, Harmonic Drives and Transmissions
• 5.3 End Effectors and Dexterous Hands
  • 5.3.1 The Dexterous Hand Market
  • 5.3.2 Why Hands Cost What They Cost
  • 5.3.3 Demand by Industry Application
  • 5.3.4 The Dexterity-Price Frontier
  • 5.3.5 Competitive Implications
• 5.4 Sensors and Perception
• 5.5 Power Systems and Operational Energy
  • 5.5.1 Power as Product
• 5.6 Semiconductors and Edge Compute
  • 5.6.1 The Memory Wall
  • 5.6.2 The Power Budget Trap
• 5.7 Operational Memory and Verifiable Autonomy
  • 5.7.1 The Requirement
  • 5.7.2 The Market Position
  • 5.7.3 The Bear Case
• 5.8 Geographic Concentration and Chokepoints

6 FOUNDATION MODELS AND ROBOT LEARNING

• 6.1 The Layer and Its Ambition
• 6.2 The Data Problem
  • 6.2.1 The Consequence for the Business Model
  • 6.2.2 Simulation as Partial Escape
• 6.3 The Vertical Integration Squeeze
• 6.4 The Inference Constraint
• 6.5 Competitive Landscape

7 HUMANOIDS

• 7.1 Market Overview
• 7.2 The Deployment Reality
• 7.3 The Three-Wave Structure
  • 7.3.1 Wave 1: Industrial
  • 7.3.2 Wave 2: Consumer and Developer
  • 7.3.3 Wave 3: Medical and Assistive
• 7.4 The Capability Gap
  • 7.4.1 The Manipulation Bottleneck
  • 7.4.2 The Step Function
• 7.5 Competitive Structure
  • 7.5.1 Why China Wins on the Current Cost Structure

8 WAREHOUSE AND LOGISTICS

• 8.1 Market Overview
• 8.2 The Task-Scripted Ceiling, and Why It Does Not Matter Here
• 8.3 The Economics: Cost Per Pick
• 8.4 What the Buyer Is Actually Buying
• 8.5 Business Model: The RaaS Transition
• 8.6 Competitive Landscape

9 MANUFACTURING AND AUTOMATION

• 9.1 Market Overview
• 9.2 The Real Cost of a Robot Is Not the Robot
• 9.3 The Batch-Size Window
• 9.4 The Labour Constraint Is Specific, Not General
• 9.5 Competitive Landscape

10 SPACE ROBOTICS

• 10.1 Market Overview
• 10.2 Why Space Cannot Cheat
• 10.3 The Radiation-Hardened Compute Gap
• 10.4 The Autonomy Reality
• 10.5 Competitive Landscape

11 CONSTRUCTION AND INFRASTRUCTURE

• 11.1 Market Overview
• 11.2 Why Construction Resisted
  • 11.2.1 The Site Is the Anti-Warehouse
  • 11.2.2 The Buyer Cannot Fund It
  • 11.2.3 The Labour Question Is Political
• 11.3 The Automation Frontier
• 11.4 Competitive Landscape

12 DEFENCE AND SECURITY

• 12.1 Market Overview
• 12.2 The Procurement Inversion
• 12.3 The Gap Between Designed and Observed Autonomy
• 12.4 The Domains
  • 12.4.1 Ground
  • 12.4.2 Air
  • 12.4.3 Maritime
  • 12.4.4 Counter-UAS
• 12.5 Company Landscape

13 COMPANY PROFILES (168 company profiles)

14 REFERENCES

List of Tables

• Table 1. Global emerging robotics market by vertical, 2027–2037 (US$ billion).
• Table 2. Classical versus emerging robotics: the four broken assumptions.
• Table 3. The seven verticals of emerging robotics.
• Table 4. The emerging robotics stack
• Table 5. Four distinct claims advanced under a single word.
• Table 6. The three questions, and the answers the bill of materials supplies.
• Table 7. Global dexterous hand market forecast, 2027–2037.
• Table 8. Dexterous hand requirements by industry application.
• Table 9. Selected foundation-model and robot-learning companies.
• Table 10. Leading humanoid manufacturers, 2027.
• Table 11. Warehouse and logistics robotics: selected companies.
• Table 12. Manufacturing and automation robotics: selected companies.
• Table 13. Space robotics: selected companies.
• Table 14. Construction and infrastructure robotics: selected companies.
• Table 15. Defence and security robotics: selected companies.

List of Figures

• Figure 1. The Emerging Robotics Market Map.
• Figure 2. The global emerging robotics market by vertical, 2027–2037 (US$ billion).
• Figure 3. Vertical positioning: 2027 market size against 2027–2037 revenue CAGR, with bubble area proportional to 2037 revenue.
• Figure 4. Humanoid bill-of-materials composition, 2027 and 2037, by share of total.
• Figure 5. The Autonomy Dependency classification (A0 to A4)
• Figure 6. Autonomy class attained by vertical, 2027: prevailing class of deployed systems versus best-in-class demonstrated.
• Figure 7. The onboard memory wall: robotic workload memory demand against the capacity of onboard accelerators.
• Figure 8. Humanoid bill-of-materials composition, 2027 and 2037, by share of total.
• Figure 9. Component cost per robot, indexed to 2027, showing differential rates of decline.
• Figure 10. Semiconductor content per humanoid robot: what the silicon in a robot actually is.
• Figure 11. Cost share against estimated gross margin, by component category, 2027.
• Figure 12. The components layer: total addressable market by category, 2027–2037 (US$ billion).
• Figure 13. Global dexterous hand market: unit shipments and revenue, 2027–2037.
• Figure 14. Dexterous hand demand by industry application, 2027 and 2037.
• Figure 15. The dexterity-price frontier: degrees of freedom required against price ceiling, by application, with bubble area proportional to 2037 demand share.
• Figure 16. The power budget trap: operational runtime against onboard compute power draw, 2027 and 2037 battery packs.
• Figure 17. Estimated Chinese share of global supply, by component category.
• Figure 18. Training data availability by modality: the robot manipulation data deficit.
• Figure 19. Foundation-model layer revenue by business model, 2027–2037.
• Figure 20. Flagship commercial humanoid deployments: units in the field.
• Figure 21. The humanoid market by adoption wave, 2027–2037 (US$ billion).
• Figure 22. Humanoid unit shipments against average selling price, 2027–2037.
• Figure 23. Humanoid market concentration and Chinese share of unit volume, 2025–2037.
• Figure 24. Warehouse and logistics robotics by sub-segment, 2027–2037 (US$ billion).
• Figure 25. The pick-rate frontier: sustained pick rate against fully-loaded cost per pick.
• Figure 26. Warehouse robotics revenue by business model, 2027–2037.
• Figure 27. Manufacturing and automation robotics by sub-segment, 2027–2037 (US$ billion).
• Figure 28. The fully-installed cost stack of one robotic work cell, 2027 and 2037.
• Figure 29. Cost per part against batch size: the addressable window for flexible robotic automation.
• Figure 30. Space robotics by segment, 2027–2037 (US$ billion).
• Figure 31. Round-trip command latency by destination, and the collapse of teleoperation.
• Figure 32. Onboard AI compute: commercial edge silicon, radiation-hardened space-qualified silicon, and the requirement for autonomous rendezvous and in-space assembly.
• Figure 33. Labour productivity, manufacturing against construction, indexed to 1970.
• Figure 34. The construction automation frontier: task repeatability against site-to-site variability.
• Figure 35. Construction and infrastructure robotics by segment, 2027–2037 (US$ billion).
• Figure 36. Defence robotics market by domain, 2027–2037 (US$ billion).
• Figure 37. Estimated unit cost by platform, against the attritability threshold.
• Figure 38. Designed autonomy class against the class observed in operational use.
• Figure 39. NEO.
• Figure 40. RAISE-A1.
• Figure 41. Agibot product line-up.
• Figure 42. Digit humanoid robot.
• Figure 43. ANYbotics robot.
• Figure 44. Apptronick Apollo.
• Figure 45. Aubo Robotics - i series.
• Figure 46. Alex.
• Figure 47. BR002.
• Figure 48. Atlas.
• Figure 49. XR-4.
• Figure 50. Deep Robotics all weather robot.
• Figure 51. Mercury X1.
• Figure 52. Prototype Ex-Robots humanoid robots.
• Figure 53. Figure.ai humanoid robot.
• Figure 54. Figure 02 humanoid robot.
• Figure 55. GR-1.
• Figure 56. Honda ASIMO.
• Figure 57. HMND 01 Alpha.
• Figure 58. IntuiCell quadruped robot.
• Figure 59. Kaleido.
• Figure 60. Forerunner.
• Figure 61. Keyper.
• Figure 62. KUKA - LBR iiwa series.
• Figure 63. Kuafu.
• Figure 64. CL-1.
• Figure 65. MagicHand S01
• Figure 66. Monumental construction robot.
• Figure 67. Neura Robotics - Cognitive Cobots.
• Figure 68. Omron - TM5-700 and TM5X-700.
• Figure 69. Tora-One.
• Figure 70. HUBO2.
• Figure 71. XBot-L.
• Figure 72. Sanctuary AI Phoenix.
• Figure 73. Astribot S1.
• Figure 74. Staubli - TX2touch series.
• Figure 75. Tesla Optimus Gen 2.
• Figure 76. Toyota T-HR3
• Figure 77. UBTECH Walker.
• Figure 78. G1 foldable robot.
• Figure 79. Unitree H1.
• Figure 80. WANDA.
• Figure 81. CyberOne.
• Figure 82. PX5.