倉儲機器人：市場佔有率分析、產業趨勢與統計、成長預測（2026-2031）

根據 Mordor Intelligence 預測，倉儲機器人市場規模將從 2025 年的 93.3 億美元成長到 2026 年的 109.6 億美元，然後在 2031 年達到 245.5 億美元，2026 年至 2031 年的複合年成長率為 17.5%。

本報告按類型（工業機器人、分類系統等）、功能（儲存、包裝等）、組件（硬體、軟體、支援和服務）、最終用戶行業（食品飲料、汽車、零售和電子商務、電氣和電子、製藥、第三方物流等）以及地區進行細分。市場預測以價值（美元）表示。

全球倉儲機器人市場趨勢及洞察

電子商務中SKU數量的激增以及當日送達的壓力

亞馬遜目前處理超過3.5億個活躍SKU，如此龐大的規模令人工揀貨員不堪重負，因此必須採用能夠可靠抓取各種形狀商品的機器人技術。當日送達承諾已將主要都市地區的配送週期縮短至四小時以內，促使亞馬遜在履約中心部署自主移動機器人（AMR），使高峰時段的訂單處理速度提升三倍。季節性需求激增時，訂單量可成長高達500%，使得彈性的人工揀貨模式成本效益低。 「貨到人（GTP）」系統消除了員工不必要的移動，而人工智慧驅動的庫存放置工具則將平均揀貨路線縮短了60%。監管機構要求企業準確揭露配送承諾，因此企業必須利用機器人技術來提高處理能力保障。

第三方物流公司和零售商加大對自主移動機器人和自動化立體倉庫的投資。

DSV累計5000萬美元在其歐洲各地部署自主移動機器人（AMR），在維持利潤率不受都市區租金上漲影響的同時，實現了85%的倉儲密度提升。沃爾瑪則承諾投入10億美元用於自動化投資，並擴大與現有門市整合的微型倉配中心的部署。 「機器人即服務（RaaS）」模式透過將支出從資本支出（CAPEX）轉移到每次揀貨的變動費用，降低了進入門檻。 ISO 3691-4無人駕駛卡車標準為規避風險的物流經理提供了合規藍圖，並正在加速AMR先導計畫的批准。

棕地維修的高資本支出與整合成本

維修現有設施的成本比待開發區設施高出 60% 至 80%。這是因為現有設施的走道、夾層和電氣設備很少與機器人的工作範圍完全吻合。專案通常需要花費 200 萬美元用於佈線、地面找平以及軟體介面。由於安裝造成的每週運作都可能導致處理量損失 5 萬美元的收入，營運商正在將部署工作分解成多個小的分階段進行，以維持運作中。供應商目前正在推廣可安裝在現有機架中的模組化設備，這不僅降低了初始資本支出，也降低了經營團隊批准的門檻。

細分市場分析

預計到2031年，行動平台將以18.02%的複合年成長率穩定成長，在待開發區履約中超越固定工業單元。受零售商為適應頻繁的SKU調整而強調佈局柔軟性的推動，移動機器人倉儲機器人市場預計到2031年將達到107.4億美元。儘管工業級六軸機械臂仍佔據重型碼垛市場34.02%的佔有率，但無輸送機自主移動機器人（AMR）策略可將基礎設施成本降低70%，並將試運行週期從數月縮短至數週。在小包裹中心，高速分類系統更受青睞，其處理能力已比2024年之前的基準值提高了40%。同時，立方體式自動化立體倉庫（AS/RS）系統使都市區的儲存密度提高了四倍。目前，一個整合層透過單一調度器協調移動機器人集群、穿梭車和升降機，從而防止通道擁塞並維持均衡的工作隊列。

在倉儲機器人市場，自主移動機器人（AMR）的混合部署方案持續受到關注。 AMR 將週轉箱運送到固定機械手臂叢集進行高精度揀選。人工智慧路徑引擎每秒重新規劃路徑，避開障礙物，並將機器人空閒時間減少到 10% 以下。供應商透過部署大型地面 AMR 進行箱體搬運，以及部署緊湊型集群機器人進行產品到人的轉移，最大限度地利用空間。工業堆垛機配備了內建視覺系統，可將堆疊模式設計時間縮短 25%，並提高負載穩定性。這對於易碎的電動車電池組至關重要。總而言之，多模態機器人集群能夠應對產品配置的變化，從而實現面向未來的營運。

儘管到2025年倉儲仍將以38.05%的銷售額佔據主導地位，但揀貨和分揀正在推動附加價值成長，預計到2031年將實現18.11%的複合年成長率。 「貨到人」原則可將工人的行走距離減少75%，從而擴大倉庫機器人在先進揀貨系統中的市場佔有率。動態貨位放置演算法可依需求預測在夜間重新安排庫存位置，將平均揀貨時間縮短至30秒。邊緣延遲現已低於30毫秒，使機器人能夠在作業過程中重新計算最佳路徑。交叉轉運中心正在投資機器人分類機，用於處理電商退貨並在當天將貨物重新投入出貨流程，從而減少因降價而造成的利潤損失。

透過預測分析將需求資料與自動化立體倉庫（AS/RS）穿梭車分配關聯起來，暢銷SKU會被放置在符合人體工學設計的揀貨站附近，從而減少日常盤點所需的工作量。機器人包裝單元即時調整紙箱尺寸，減少15%的紙板浪費，並最佳化卡車裝載率。在食品履約領域，重量波動會影響輸送機速度，因此分箱自動化正變得越來越普遍。操作員認為揀貨效率是一個瓶頸，因此需要增加對基於視覺的末端執行器和自動揀貨車的投資，以彌補這一差距。

區域分析

預計到2025年，亞太地區將佔全球銷售額的39.52%，並在2031年之前以17.94%的複合年成長率成長，這主要得益於中國製造商強勁的出口和區域工資水平的上漲。 Geek+等本土巨頭已創下出貨量新高；日本正轉向機器人技術以應對勞動力老化問題；韓國則在其國家產業政策的指導下，將自動化立體倉庫（AS/RS）系統整合到智慧工廠中。印度正進入加速成長階段，並透過政府支持的自動化補貼吸引外國直接投資。

北美位居第二，繼續保持其作為創業投資驅動型創新標竿的地位，預計2024年將有超過20億美元投資於倉儲自動化新創公司。美國大型零售商率先採用微型倉配和暗店概念，而加拿大的多倫多-溫哥華走廊正在擴大機器人技術的應用，以緩解勞動力短缺問題。墨西哥則受惠於近岸外包，透過部署配備自主移動機器人（AMR）的倉庫，為美國進口商降低了25%的收貨成本。

儘管歐洲在顯著成長方面落後於其他國家，但其應用正在穩步推進。德國正利用工業4.0津貼為汽車零件供應商提供整合物流的資金籌措。英國優先發展可靈活調整的系統，以適應脫歐後的海關流程。法國和荷蘭作為泛歐門戶，正在投資興建立方體倉庫，以緩解土地資源緊張的局面。歐盟即將訂定的人工智慧法案將提高安全標準，並優先考慮成熟可靠的供應商，但同時也增加合規成本。

其他好處：

• Excel格式的市場預測（ME）表
• 3個月的分析師支持

目錄

第1章：引言

• 研究假設和市場定義
• 調查範圍

第2章：調查方法

第3章執行摘要

第4章 市場狀況

• 市場概覽
• 市場促進因素
  • 電子商務中SKU數量的激增以及當日送達的壓力
  • 第三方物流公司和零售商加大對自主移動機器人（AMR）和自動化立體倉庫（AS/RS）的投資
  • 經合組織國家倉儲勞動力減少
  • 人工智慧視覺技術使機器人能夠揀選「難以處理」的SKU。
  • 基於邊緣的集群編配可減少停機時間並提高投資回報率。
  • 隨著碳中和倉庫運作的強制實施，低能耗機器人正受到關注。
• 市場限制因素
  • 與棕地維修相關的高額資本支出（CAPEX）及整合成本。
  • 各地安全和資料隱私法規不盡相同
  • 車輛管理軟體中的網實整合安全漏洞
  • 鋰離子電池供應的波動正在影響 AMR 的物料清單 (BOM) 成本。
• 產業價值鏈分析
• 監理情勢
• 技術展望
• 波特五力分析

第5章 市場規模與成長預測

• 按類型
  • 工業機器人
  • 分類系統
  • 輸送帶
  • 堆垛機
  • 自動化倉庫系統（AS/RS）
  • 移動機器人（AGV 和 AMR）
• 按功能
  • 貯存
  • 包裝
  • 轉運
  • 揀貨和分類
• 按組件
  • 硬體
  • 軟體
  • 支援和服務
• 按最終用戶行業分類
  • 食品/飲料
  • 車
  • 零售與電子商務
  • 電氣和電子設備
  • 製藥
  • 第三方物流（3PL）
  • 其他終端用戶產業
• 按地區
  • 北美洲
    • 美國
    • 加拿大
  • 南美洲
    • 巴西
    • 阿根廷
    • 其他南美國家
  • 歐洲
    • 德國
    • 英國
    • 法國
    • 義大利
    • 其他歐洲國家
  • 亞太地區
    • 中國
    • 日本
    • 韓國
    • 印度
    • 其他亞太國家
  • 中東和非洲
    • 中東
      • 沙烏地阿拉伯
      • 阿拉伯聯合大公國
      • 土耳其
      • 其他中東國家
    • 非洲
      • 南非
      • 奈及利亞
      • 其他非洲國家

第6章 競爭情勢

• 市場集中度
• 策略趨勢
• 市佔率分析
• 公司簡介
  • ABB Ltd.
  • Amazon Robotics LLC
  • TGW Logistics Group GmbH
  • ST Engineering Ltd.（Aethon Inc.）
  • inVia Robotics, Inc.
  • FANUC Corporation
  • Honeywell International Inc.
  • Toshiba Corporation
  • OMRON Corporation
  • Yaskawa Electric Corporation
  • KUKA AG
  • Fetch Robotics, Inc.（Zebra）
  • Geekplus Technology Co., Ltd.
  • GreyOrange Pte. Ltd.
  • Hangzhou Hikrobot Technology Co., Ltd.
  • Syrius Robotics Co., Ltd.
  • Locus Robotics Corp.
  • Daifuku Co., Ltd.
  • Dematic Corp.（KION Group AG）
  • Swisslog Holding AG
  • Boston Dynamics, Inc.
  • Exotec SAS
  • Symbotic Inc.
  • Teradyne, Inc.（Mobile Industrial Robots A/S）
  • Zebra Technologies Corporation

第7章 市場機會與未來展望

According to Mordor Intelligence, the warehouse robotics market size is expected to grow from USD 9.33 billion in 2025 to USD 10.96 billion in 2026 and is forecast to reach USD 24.55 billion by 2031 at 17.5% CAGR over 2026-2031.

This report is Segmented by Type (Industrial Robots, Sortation Systems, and More), Function (Storage, Packaging, and More), Component (Hardware, Software, and Support and Services), End-User Industry (Food and Beverage, Automotive, Retail and E-Commerce, Electrical and Electronics, Pharmaceutical, 3PL, and More), and Geography. The Market Forecasts are Provided in Terms of Value (USD).

Global Warehouse Robotics Market Trends and Insights

E-commerce SKU Proliferation and Same-Day-Delivery Pressure

Amazon now juggles more than 350 million active SKUs, a scale that overwhelms manual pickers and demands robotic confidence in grasping dissimilar shapes. Same-day commitments shrink cycle times to under four hours in major metros, so fulfillment nodes deploy AMRs that triple order-processing speed during peak events. Seasonal spikes can push volumes 500%, rendering manual flex-labor models cost-prohibitive. Goods-to-person systems erase unproductive employee travel, while AI inventory-placement tools cut average pick paths 60%. Regulators enforce truthful delivery-promise disclosure, compelling operators to harden throughput guarantees with robotic capacity.

Rising Investments by 3PLs and Retailers in AMRs and AS/RS

DSV earmarked USD 50 million to roll out AMRs across European sites, unlocking density gains of 85% and shielding margins from urban rent inflation. Walmart matched with a USD 1 billion automation pledge that widens adoption of micro-fulfillment centers embedded in existing stores. Robots-as-a-service schemes lower entry thresholds by shifting spend from CAPEX to variable fees per pick. ISO 3691-4 driverless-truck standards give risk-averse logistics managers a compliance roadmap, accelerating green-lighting of AMR pilot projects.

High CAPEX and Integration Cost for Brownfield Retrofits

Retrofitting legacy sites costs 60-80% more than greenfield builds because aisles, mezzanines, and electrical services rarely align with robot envelopes. Projects often trigger USD 2 million in wiring, floor leveling, and software-interface expenses. Every week of installation downtime can forfeit USD 50,000 in throughput revenue, so operators stagger rollouts in micro-phases that preserve live lanes. Vendors now push modular pods that fit inside existing racks, trimming upfront cash burn and easing board-level approvals.

Other drivers and restraints analyzed in the detailed report include:

1. Shrinking Warehouse Labor Pool in OECD Economies
2. AI-Powered Vision Enabling Robotic Picking of Difficult SKUs
3. Fragmented Safety and Data-Privacy Regulations by Region

For complete list of drivers and restraints, kindly check the Table Of Contents.

Segment Analysis

Mobile platforms edge forward with an 18.02% CAGR to 2031, eclipsing fixed industrial units for greenfield fulfillment projects. The warehouse robotics market size for mobile robots is projected to reach USD 10.74 billion by 2031 as retailers value layout agility that supports frequent SKU resets. Industrial six-axis arms still own heavy palletizing with 34.02% share, yet conveyor-less AMR strategies cut infrastructure costs 70% and shrink commissioning times from months to weeks. Parcel hubs favor high-speed sortation systems that already handle 40% more packages than pre-2024 baselines, while cube-based AS/RS lifts storage density fourfold in urban footprints. Integration layers now orchestrate mobile fleets, shuttles, and lifts under one scheduler to prevent aisle congestion and balance work queues.

The warehouse robotics market continues to showcase hybrid deployments where AMRs ferry totes to stationary arm clusters for high-dexterity picks. AI route engines re-plan paths every second to dodge obstacles and reduce robot idle to under 10%. Vendors position large-format floor AMRs for case movement and compact swarm bots for goods-to-person tasks, maximizing cube utilization. Industrial palletizers gain embedded vision that trims pattern design times 25% and improves load stability, vital for fragile EV battery packs. Collectively, multi-modal fleets future-proof operations against product-mix volatility.

Storage still dominates with 38.05% slice of 2025 revenue, yet picking and sorting drives incremental value and will post an 18.11% CAGR to 2031. The warehouse robotics market share for advanced picking systems rises as goods-to-person principles cut worker walk distances 75%. Dynamic slotting algorithms reposition inventory overnight based on forecast demand, shrinking average pick span to 30 seconds. Edge latency now measures below 30 milliseconds, letting robots recalculate optimal routes mid-mission. Cross-dock nodes invest in robotic sorters that process e-commerce returns and re-inject goods into outbound flows the same day, limiting markdown erosion.

Predictive analytics tie demand data to AS/RS shuttle assignments, pushing high-velocity SKUs near ergonomic pick stations and lowering daily cycle-count labor. Robotics packaging cells adapt box size in real time, cutting corrugate waste 15% and optimizing truck fill rates. Split-case automation gains traction in grocery fulfillment where variable weight items challenge conveyor pacing. Operators view picking performance as the rate-limiting step, and capital therefore gravitates toward vision-equipped end-effectors and autonomous carts that close the gap.

Complete Report Scope:

• By Type
  • Industrial Robots
  • Sortation Systems
  • Conveyors
  • Palletizers
  • Automated Storage and Retrieval Systems (AS/RS)
  • Mobile Robots (AGVs and AMRs)
• By Function
  • Storage
  • Packaging
  • Trans-shipment
  • Picking and Sorting
• By Component
  • Hardware
  • Software
  • Support and Services
• By End-user Industry
  • Food and Beverage
  • Automotive
  • Retail and E-commerce
  • Electrical and Electronics
  • Pharmaceutical
  • Third-Party Logistics (3PL)
  • Other End-user Industries
• By Geography
  • North America
    • United States
    • Canada
  • South America
    • Brazil
    • Argentina
    • Rest of South America
  • Europe
    • Germany
    • United Kingdom
    • France
    • Italy
    • Rest of Europe
  • Asia-Pacific
    • China
    • Japan
    • South Korea
    • India
    • Rest of Asia-Pacific
  • Middle East and Africa
    • Middle East
      • Saudi Arabia
      • United Arab Emirates
      • Turkey
      • Rest of Middle East
    • Africa
      • South Africa
      • Nigeria
      • Rest of Africa

Geography Analysis

Asia Pacific retained 39.52% of global revenue in 2025 and is tracking an 17.94% CAGR to 2031 as Chinese makers export aggressively and regional wages climb. Local champions such as Geek+ shipped record volumes while Japan turned to robotics to offset an aging workforce and South Korea integrated AS/RS with smart factories under national industrial policy. India enters an acceleration phase on the back of government-backed automation subsidies that attract foreign direct investment.

North America ranks second and remains a bellwether for venture-backed innovation, channeling more than USD 2 billion into warehouse automation startups during 2024. U.S. big-box retailers pioneer micro-fulfillment and dark-store concepts, while Canada's Toronto-Vancouver corridor scales robotics to relieve labor scarcity. Mexico benefits from near-shoring and deploys AMR-ready warehouses that cut landed costs for U.S. importers by 25%.

Europe lags headline growth yet maintains steady adoption. Germany leans on Industry 4.0 grants to fund integrated logistics cells for automotive suppliers. The United Kingdom prioritizes flexible systems that can realign to post-Brexit customs flows. France and the Netherlands act as pan-European gateways, investing in cube-storage to mitigate land constraints. The EU's forthcoming AI Act will raise compliance costs yet elevate safety baselines, favoring established vendors with proven records.

1. ABB Ltd.
2. Amazon Robotics LLC
3. TGW Logistics Group GmbH
4. ST Engineering Ltd. (Aethon Inc.)
5. inVia Robotics, Inc.
6. FANUC Corporation
7. Honeywell International Inc.
8. Toshiba Corporation
9. OMRON Corporation
10. Yaskawa Electric Corporation
11. KUKA AG
12. Fetch Robotics, Inc. (Zebra)
13. Geekplus Technology Co., Ltd.
14. GreyOrange Pte. Ltd.
15. Hangzhou Hikrobot Technology Co., Ltd.
16. Syrius Robotics Co., Ltd.
17. Locus Robotics Corp.
18. Daifuku Co., Ltd.
19. Dematic Corp. (KION Group AG)
20. Swisslog Holding AG
21. Boston Dynamics, Inc.
22. Exotec SAS
23. Symbotic Inc.
24. Teradyne, Inc. (Mobile Industrial Robots A/S)
25. Zebra Technologies Corporation

Additional Benefits:

• The market estimate (ME) sheet in Excel format
• 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

• 1.1 Study Assumptions and Market Definition
• 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET LANDSCAPE

• 4.1 Market Overview
• 4.2 Market Drivers
  • 4.2.1 E-commerce SKU proliferation and same-day-delivery pressure
  • 4.2.2 Rising investments by 3PLs and retailers in AMRs and AS/RS
  • 4.2.3 Shrinking warehouse labor pool in OECD economies
  • 4.2.4 AI-powered vision enabling robotic picking of "difficult" SKUs
  • 4.2.5 Edge-based fleet orchestration cuts downtime and boosts ROI
  • 4.2.6 Carbon-neutral warehousing mandates favor low-energy robots
• 4.3 Market Restraints
  • 4.3.1 High CAPEX and integration cost for brownfield retrofits
  • 4.3.2 Fragmented safety and data-privacy regulations by region
  • 4.3.3 Cyber-physical security vulnerabilities in fleet software
  • 4.3.4 Lithium-ion battery supply volatility affects AMR BOM costs
• 4.4 Industry Value Chain Analysis
• 4.5 Regulatory Landscape
• 4.6 Technological Outlook
• 4.7 Porter's Five Forces Analysis
  • 4.7.1 Bargaining Power of Buyers
  • 4.7.2 Bargaining Power of Suppliers
  • 4.7.3 Threat of New Entrants
  • 4.7.4 Threat of Substitute Products
  • 4.7.5 Intensity of Competitive Rivalry

5 MARKET SIZE AND GROWTH FORECASTS (VALUE)

• 5.1 By Type
  • 5.1.1 Industrial Robots
  • 5.1.2 Sortation Systems
  • 5.1.3 Conveyors
  • 5.1.4 Palletizers
  • 5.1.5 Automated Storage and Retrieval Systems (AS/RS)
  • 5.1.6 Mobile Robots (AGVs and AMRs)
• 5.2 By Function
  • 5.2.1 Storage
  • 5.2.2 Packaging
  • 5.2.3 Trans-shipment
  • 5.2.4 Picking and Sorting
• 5.3 By Component
  • 5.3.1 Hardware
  • 5.3.2 Software
  • 5.3.3 Support and Services
• 5.4 By End-user Industry
  • 5.4.1 Food and Beverage
  • 5.4.2 Automotive
  • 5.4.3 Retail and E-commerce
  • 5.4.4 Electrical and Electronics
  • 5.4.5 Pharmaceutical
  • 5.4.6 Third-Party Logistics (3PL)
  • 5.4.7 Other End-user Industries
• 5.5 By Geography
  • 5.5.1 North America
    • 5.5.1.1 United States
    • 5.5.1.2 Canada
  • 5.5.2 South America
    • 5.5.2.1 Brazil
    • 5.5.2.2 Argentina
    • 5.5.2.3 Rest of South America
  • 5.5.3 Europe
    • 5.5.3.1 Germany
    • 5.5.3.2 United Kingdom
    • 5.5.3.3 France
    • 5.5.3.4 Italy
    • 5.5.3.5 Rest of Europe
  • 5.5.4 Asia-Pacific
    • 5.5.4.1 China
    • 5.5.4.2 Japan
    • 5.5.4.3 South Korea
    • 5.5.4.4 India
    • 5.5.4.5 Rest of Asia-Pacific
  • 5.5.5 Middle East and Africa
    • 5.5.5.1 Middle East
      • 5.5.5.1.1 Saudi Arabia
      • 5.5.5.1.2 United Arab Emirates
      • 5.5.5.1.3 Turkey
      • 5.5.5.1.4 Rest of Middle East
    • 5.5.5.2 Africa
      • 5.5.5.2.1 South Africa
      • 5.5.5.2.2 Nigeria
      • 5.5.5.2.3 Rest of Africa

6 COMPETITIVE LANDSCAPE

• 6.1 Market Concentration
• 6.2 Strategic Moves
• 6.3 Market Share Analysis
• 6.4 Company Profiles (includes Global level Overview, Market level overview, Core Segments, Financials as available, Strategic Information, Market Rank/Share, Products and Services, Recent Developments)
  • 6.4.1 ABB Ltd.
  • 6.4.2 Amazon Robotics LLC
  • 6.4.3 TGW Logistics Group GmbH
  • 6.4.4 ST Engineering Ltd. (Aethon Inc.)
  • 6.4.5 inVia Robotics, Inc.
  • 6.4.6 FANUC Corporation
  • 6.4.7 Honeywell International Inc.
  • 6.4.8 Toshiba Corporation
  • 6.4.9 OMRON Corporation
  • 6.4.10 Yaskawa Electric Corporation
  • 6.4.11 KUKA AG
  • 6.4.12 Fetch Robotics, Inc. (Zebra)
  • 6.4.13 Geekplus Technology Co., Ltd.
  • 6.4.14 GreyOrange Pte. Ltd.
  • 6.4.15 Hangzhou Hikrobot Technology Co., Ltd.
  • 6.4.16 Syrius Robotics Co., Ltd.
  • 6.4.17 Locus Robotics Corp.
  • 6.4.18 Daifuku Co., Ltd.
  • 6.4.19 Dematic Corp. (KION Group AG)
  • 6.4.20 Swisslog Holding AG
  • 6.4.21 Boston Dynamics, Inc.
  • 6.4.22 Exotec SAS
  • 6.4.23 Symbotic Inc.
  • 6.4.24 Teradyne, Inc. (Mobile Industrial Robots A/S)
  • 6.4.25 Zebra Technologies Corporation

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK

• 7.1 White-space and Unmet-need Assessment