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市場調查報告書
商品編碼
2144389

2034年自主物料輸送市場預測－全球分析（依物料輸送類型、導航技術、組件、操作模式、最終用戶和地區分類）

Autonomous Material Handling Market Forecasts to 2034 - Global Analysis By Material Handling Type, Navigation Technology, Component, Operation, End User, and Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的數據，預計到 2026 年，全球自主物料輸送市場規模將達到 65 億美元，並在預測期內以 13.7% 的複合年成長率成長，到 2034 年將達到 182 億美元。

自主物料輸送包括自主移動機器人、自動導引運輸車(AGV)、自主堆高機、機械臂和自主輸送機，這些設備配備了基於雷射雷達 (LiDAR)、視覺、磁導航、反射器導航和即時定位與地圖構建 (SLAM) 等導航技術。這些系統可在製造、零售和電子商務、食品飲料、製藥以及物流倉儲等環境中執行揀選、運輸、分類、裝卸和儲存/檢索等作業。硬體、軟體、感測器、控制系統和通訊系統的結合實現了靈活且擴充性的自動化，無需固定基礎設施。日益嚴重的勞動力短缺和對靈活自動化日益成長的需求正在推動全球自主物料輸送市場的發展。

市場動態

人手不足加劇和人事費用上升

倉儲和製造業長期存在的人手不足，正推動自動化物料輸送系統的應用，這些系統無需依賴人工即可維持處理能力。已開發經濟體人事費用的不斷上漲，使得自動化與人工操作相比，成本競爭力日益增強。電子商務交易量的成長，催生了對靈活搬運系統的需求，這些系統能夠在旺季快速擴展規模，而無需相應增加勞動力。限制人工搬運重物的安全法規，也加速了工業環境中自動化的應用。重複性物料輸送工作中員工流動率低，進一步強化了自動化的合理性。

巨額資本投資與整合的複雜性

自主物料輸送車輛需要大量的資本投入，這對資金有限的中型企業來說尤其構成重大障礙。與現有倉庫管理系統、輸送機和設施基礎設施整合的複雜性會延長部署週期並增加專案風險。自動駕駛汽車平臺之間缺乏足夠的標準化，導致多供應商部署中的互通性問題。設施維修要求，例如地面準備、充電基礎設施和交通管理，也會推高專案總成本。對於小規模企業而言，投資回報期的不確定性限制了其採用。

SLAM導航和艦隊編配的進步

同步定位與地圖建置 (SLAM) 導航技術的進步使自動駕駛車輛運作，而無需對固定基礎設施維修。先進的車隊編配軟體的開發使得大規模設施內不同車輛群的高效協調成為可能。機器人即服務 (RaaS) 模式的日益普及降低了初​​始投資成本並擴大了目標市場。與倉庫執行系統 (WES) 的整合實現了從收貨到出貨的全面自動化解決方案。電池技術的進步和機器充電技術的引入延長了設備的運作。

與傳統自動化和人工操作的競爭

與傳統輸送機式自動化和人工操作的競爭可能會限制自主系統在柔軟性要求高於成本的應用領域的普及。經濟壓力可能導致企業延遲自動化投資，延長設備使用壽命。科技的複雜性可能會削弱企業信心，減緩科技普及速度。對失業的擔憂可能會導致企業內部對自動化專案的抵制。科技的快速發展也為早期採用者帶來了技術過時的風險。

新型冠狀病毒（COVID-19）的影響：

新冠疫情大大加速了自動化物料輸送的應用，因為許多企業在勞動力短缺和需要保持社交距離的情況下，仍力求維持營運。疫情封鎖期間電子商務交易的激增暴露了人工處理能力的局限性，促使企業迫切需要投資自動化。即使在疫情後時期，隨著企業意識到自動化系統的容錯優勢，自動化技術的應用仍在持續。疫情後勞動力市場的緊張進一步鞏固了自動化的經濟可行性。對業務連續性的日益關注也持續推動著科技的應用。

在預測期內，自主移動機器人（AMR）細分市場預計將佔據最大的市場佔有率。

預計在預測期內，自主移動機器人（AMR）細分市場將佔據最大的市場佔有率。這是因為在所有自主運輸技術中，AMR 具有最高的柔軟性和最低的基礎設施要求。履約、製造業和醫療保健等領域的廣泛應用正在推動市場顯著成長。導航技術的進步使得 AMR 即使在動態環境中也能與人類員工可靠地協同工作。更低的單位成本正在將目標市場擴展到小規模企業。 AMR 透過取代人力和提高處理能力，能夠快速實現投資回報。

預計在預測期內，基於 SLAM 的導航領域將呈現最高的複合年成長率。

在預測期內，基於SLAM的導航領域預計將呈現最高的成長率，這主要得益於市場對無需基礎設施、可快速部署和重新配置的導航系統的需求不斷成長。 SLAM技術使自動駕駛車輛能夠即時建立和更新周圍環境地圖，而無需反射器、磁帶或其他固定基礎設施。在佈局不斷變化的動態環境中不斷擴展的部署也推動了該領域的成長。感測器融合和運算能力的進步提高了SLAM的可靠性並降低了成本。無需基礎設施的部署顯著降低了專案的總成本和部署時間。

市佔率最大的地區：

在預測期內，北美預計將佔據最大的市場佔有率，這主要得益於其高昂的人事費用、先進的物流基礎設施以及眾多自主物料輸送供應商的強大實力。美國擁有眾多領先的自主移動機器人（AMR）和自動導引車（AGV）製造商，這些製造商在電子商務、製造業和醫療保健領域擁有卓越的業績記錄。高電子商務滲透率和緊張的勞動力市場進一步鞏固了其在該地區市場的領先地位。倉儲和物流營運領域的大規模自動化投資也推動了相關技術的應用。

複合年成長率最高的地區：

在預測期內，亞太地區預計將呈現最高的複合年成長率，這主要得益於主要經濟體電子商務的快速擴張、製造業的成長以及人事費用的上升。中國、日本和韓國正在大力投資倉儲自動化，其中自動駕駛運輸是核心。物流基礎設施的改善，加上政府對機器人技術的支持，正在加速市場成長。東南亞製造業產能的擴張也創造了巨大的新需求。

免費客製化服務：

所有購買此報告的客戶均可從以下免費自訂選項中選擇一項：

  • 企業概況
    • 對其他市場參與者（最多 3 家公司）進行全面分析
    • 對主要公司進行SWOT分析（最多3家公司）
  • 區域細分
    • 根據客戶的興趣，我們將提供主要國家的市場估算和預測，以及複合年成長率（註：需經可行性確認）。
  • 競爭性標竿分析
    • 根據產品系列、企業發展和策略聯盟對重點公司進行基準分析。

目錄

第1章執行摘要

  • 市場概覽及主要亮點
  • 促進因素、挑戰與機遇
  • 競爭格局概述
  • 戰略洞察與建議

第2章：研究框架

  • 研究目標和範圍
  • 相關人員分析
  • 研究假設和限制
  • 調查方法

第3章 市場動態與趨勢分析

  • 市場定義與結構
  • 主要市場促進因素
  • 市場限制與挑戰
  • 投資成長機會和重點領域
  • 產業威脅與風險評估
  • 技術與創新展望
  • 新興市場/高成長市場
  • 監管和政策環境
  • 新冠疫情的影響及復甦前景

第4章：競爭環境與策略評估

  • 波特五力分析
    • 供應商的議價能力
    • 買方的議價能力
    • 替代品的威脅
    • 新進入者的威脅
    • 競爭公司之間的競爭
  • 主要公司市佔率分析
  • 產品基準評效和效能比較

第5章 全球自主物料輸送市場：依物料輸送類型分類

  • 自主移動機器人
  • 自動導引運輸車（AGV）
  • 自動堆高機
  • 機械臂
  • 自主輸送機
  • 其他類型的物料輸送

第6章 全球自主物料輸送市場：依導航技術分類

  • 基於LiDAR的導航
  • 基於視覺的導航
  • 磁導航
  • 利用反射鏡進行導航
  • 基於SLAM的導航
  • 其他導航技術

第7章 全球自主物料輸送市場：依組件分類

  • 硬體
  • 軟體
  • 感應器
  • 控制系統
  • 通訊系統
  • 其他規則

第8章 全球自主物料輸送市場：依營運方式分類

  • 挑選
  • 運輸
  • 排序
  • 裝卸
  • 儲存和檢索
  • 其他工作

第9章 全球自主物料輸送市場：依最終用戶分類

  • 製造業
  • 零售與電子商務
  • 食品/飲料
  • 製藥
  • 物流/倉儲
  • 其他最終用戶

第10章 全球自主物料輸送市場：依地區分類

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 英國
    • 德國
    • 法國
    • 義大利
    • 西班牙
    • 荷蘭
    • 比利時
    • 瑞典
    • 瑞士
    • 波蘭
    • 其他歐洲國家
  • 亞太地區
    • 中國
    • 日本
    • 印度
    • 韓國
    • 澳洲
    • 印尼
    • 泰國
    • 馬來西亞
    • 新加坡
    • 越南
    • 其他亞太國家
  • 南美洲
    • 巴西
    • 阿根廷
    • 哥倫比亞
    • 智利
    • 秘魯
    • 其他南美國家
  • 世界其他地區（RoW）
    • 中東
      • 沙烏地阿拉伯
      • 阿拉伯聯合大公國
      • 卡達
      • 以色列
      • 其他中東國家
    • 非洲
      • 南非
      • 埃及
      • 摩洛哥
      • 其他非洲國家

第11章 策略市場資訊

  • 工業價值網路和供應鏈評估
  • 空白區域和機會地圖
  • 產品演進與市場生命週期分析
  • 通路、經銷商和打入市場策略的評估

第12章 產業趨勢與策略舉措

  • 併購
  • 夥伴關係、聯盟和合資企業
  • 新產品發布和認證
  • 擴大生產能力和投資
  • 其他策略舉措

第13章：公司簡介

  • Daifuku Co., Ltd.
  • Dematic GmbH
  • KION Group AG
  • Jungheinrich AG
  • Toyota Industries Corporation
  • Honeywell International Inc.
  • ABB Ltd.
  • Siemens AG
  • Ocado Group plc
  • Geekplus Technology Co., Ltd.
  • Locus Robotics Corporation
  • Seegrid Corporation
  • OTTO Motors
  • Balyo
  • Exotec
Product Code: SMRC39829

According to Stratistics MRC, the Global Autonomous Material Handling Market is accounted for $6.5 billion in 2026 and is expected to reach $18.2 billion by 2034 growing at a CAGR of 13.7% during the forecast period. Autonomous material handling encompasses autonomous mobile robots, automated guided vehicles, autonomous forklifts, robotic arms, and autonomous conveyors equipped with LiDAR-based navigation, vision-based navigation, magnetic navigation, reflector-based navigation, and SLAM-based navigation technologies. These systems perform picking, transporting, sorting, loading and unloading, and storage and retrieval operations across manufacturing, retail and e-commerce, food and beverage, pharmaceutical, and logistics and warehousing environments. Hardware, software, sensors, control systems, and communication systems combine to deliver flexible, scalable automation without fixed infrastructure. Growing labor shortages and demand for flexible automation are driving the global autonomous material handling market.

Market Dynamics

Driver:

Growing labor shortages and rising wage costs

Persistent labor shortages across warehousing and manufacturing operations are driving adoption of autonomous material handling systems that maintain throughput without dependency on human labor availability. Rising wage costs across developed economies are making automation increasingly cost-competitive relative to manual operations. Growing e-commerce volumes require flexible handling systems capable of scaling rapidly during peak periods without proportional labor increases. Safety regulations limiting manual handling of heavy loads accelerate adoption in industrial environments. Worker retention challenges in repetitive material handling roles further reinforce the economic case for automation.

Restraint:

High capital investment and integration complexity

High capital investment requirements for autonomous material handling fleets present significant barriers, particularly for mid-sized operations with constrained capital budgets. Integration complexity with existing warehouse management systems, conveyors, and facility infrastructure extends deployment timelines and increases project risk. Limited standardization across autonomous vehicle platforms creates interoperability challenges for multi-vendor deployments. Facility modification requirements including floor preparation, charging infrastructure, and traffic management add to total project costs. Uncertain payback periods in low-volume operations limit adoption.

Opportunity:

Advances in SLAM navigation and fleet orchestration

Advances in simultaneous localization and mapping navigation technologies are enabling autonomous vehicles to operate in dynamic environments without fixed infrastructure modifications. Development of sophisticated fleet orchestration software enables efficient coordination of mixed fleets across large facilities. Growing availability of robotics-as-a-service models reduces upfront capital requirements and expands addressable markets. Integration with warehouse execution systems creates comprehensive automation solutions spanning receiving through shipping. Advances in battery technology and opportunity charging extend operational availability.

Threat:

Competition from traditional automation and manual operations

Competition from traditional conveyor-based automation and manual operations may limit adoption in applications where flexibility requirements do not justify autonomous system costs. Economic pressures may cause operators to delay automation investments and extend equipment lifecycles. Technology complexity may erode operator confidence and slow implementation velocity. Workforce displacement concerns may generate organizational resistance to automation programs. Rapid technology evolution creates obsolescence risk for early adopters.

Covid-19 Impact:

The COVID-19 pandemic dramatically accelerated adoption of autonomous material handling as facilities sought to maintain operations despite workforce disruptions and social distancing requirements. E-commerce volume surges during lockdown periods exposed capacity limitations of manual operations and drove urgent automation investment. The post-pandemic period has witnessed sustained adoption as operators recognize the resilience benefits of autonomous systems. Labor market tightness following the pandemic reinforced the economic case for automation. Growing focus on operational continuity continues driving technology adoption.

The autonomous mobile robots segment is expected to be the largest during the forecast period

The autonomous mobile robots segment is expected to account for the largest market share during the forecast period as AMRs offer the greatest flexibility and lowest infrastructure requirements among autonomous handling technologies. Growing adoption across e-commerce fulfillment, manufacturing, and healthcare applications drives substantial market volume. Advances in navigation technology enable reliable operation in dynamic environments alongside human workers. Declining unit costs are expanding addressable markets to smaller operations. AMRs deliver rapid return on investment through labor substitution and throughput improvement.

The SLAM-based navigation segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the SLAM-based navigation segment is predicted to witness the highest growth rate driven by increasing demand for infrastructure-free navigation enabling rapid deployment and reconfiguration. SLAM technology enables autonomous vehicles to build and update maps of their environment in real time without requiring reflectors, magnetic tape, or other fixed infrastructure. Growing adoption in dynamic environments with changing layouts supports segment growth. Advances in sensor fusion and computing power are improving SLAM reliability and reducing costs. Infrastructure-free deployment substantially reduces total project cost and implementation time.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share owing to high labor costs, advanced logistics infrastructure, and strong presence of autonomous material handling providers. The United States hosts major AMR and AGV manufacturers with established deployments across e-commerce, manufacturing, and healthcare sectors. High e-commerce penetration and labor market tightness reinforce regional market leadership. Significant automation investment across warehousing and distribution operations drives adoption.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR driven by rapid e-commerce expansion, manufacturing growth, and increasing labor costs across major economies. China, Japan, and South Korea are investing heavily in warehouse automation with autonomous handling as a core component. Growing logistics infrastructure development and government support for robotics accelerate market growth. Expanding manufacturing capacity across Southeast Asia creates substantial new demand.

Key players in the market

Some of the key players in the Autonomous Material Handling Market include Daifuku Co., Ltd., Dematic GmbH, KION Group AG, Jungheinrich AG, Toyota Industries Corporation, Honeywell International Inc., ABB Ltd., Siemens AG, Ocado Group plc, Geekplus Technology Co., Ltd., Locus Robotics Corporation, Seegrid Corporation, OTTO Motors, Balyo, and Exotec.

Key Developments:

In July 2026, Locus Robotics Corporation introduced a next-generation AMR fleet featuring advanced SLAM navigation and AI-powered traffic optimization, enabling 40% higher throughput in high-density fulfillment operations.

In March 2026, Daifuku Co., Ltd. launched an integrated autonomous material handling platform combining AMRs, robotic arms, and automated storage for end-to-end warehouse automation in cold chain applications.

In October 2025, Geekplus Technology Co., Ltd. expanded its autonomous mobile robot portfolio with new high-payload models designed for heavy manufacturing and automotive applications, supporting loads up to 1,500 kilograms.

In May 2025, Seegrid Corporation announced significant enhancements to its autonomous forklift technology featuring improved pallet recognition and autonomous trailer loading capabilities.

In August 2024, Honeywell International Inc. launched an autonomous material handling solution integrating robotic arms with mobile robots for mixed-case picking applications in distribution centers.

Material Handling Types Covered:

  • Autonomous Mobile Robots
  • Automated Guided Vehicles
  • Autonomous Forklifts
  • Robotic Arms
  • Autonomous Conveyors
  • Other Material Handling Types

Navigation Technologies Covered:

  • LiDAR-Based Navigation
  • Vision-Based Navigation
  • Magnetic Navigation
  • Reflector-Based Navigation
  • SLAM-Based Navigation
  • Other Navigation Technologies

Components Covered:

  • Hardware
  • Software
  • Sensors
  • Control Systems
  • Communication Systems
  • Other Components

Operations Covered:

  • Picking
  • Transporting
  • Sorting
  • Loading & Unloading
  • Storage & Retrieval
  • Other Operations

End Users Covered:

  • Manufacturing
  • Retail & E-Commerce
  • Food & Beverage
  • Pharmaceuticals
  • Logistics & Warehousing
  • Other End Users

Regions Covered:

  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • United Kingdom
    • Germany
    • France
    • Italy
    • Spain
    • Netherlands
    • Belgium
    • Sweden
    • Switzerland
    • Poland
    • Rest of Europe
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Australia
    • Indonesia
    • Thailand
    • Malaysia
    • Singapore
    • Vietnam
    • Rest of Asia Pacific
  • South America
    • Brazil
    • Argentina
    • Colombia
    • Chile
    • Peru
    • Rest of South America
  • Rest of the World (RoW)
    • Middle East
  • Saudi Arabia
  • United Arab Emirates
  • Qatar
  • Israel
  • Rest of Middle East
    • Africa
  • South Africa
  • Egypt
  • Morocco
  • Rest of Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2023, 2024, 2025, 2026, 2027, 2028, 2030, 2032 and 2034
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

  • 1.1 Market Snapshot and Key Highlights
  • 1.2 Growth Drivers, Challenges, and Opportunities
  • 1.3 Competitive Landscape Overview
  • 1.4 Strategic Insights and Recommendations

2 Research Framework

  • 2.1 Study Objectives and Scope
  • 2.2 Stakeholder Analysis
  • 2.3 Research Assumptions and Limitations
  • 2.4 Research Methodology
    • 2.4.1 Data Collection (Primary and Secondary)
    • 2.4.2 Data Modeling and Estimation Techniques
    • 2.4.3 Data Validation and Triangulation
    • 2.4.4 Analytical and Forecasting Approach

3 Market Dynamics and Trend Analysis

  • 3.1 Market Definition and Structure
  • 3.2 Key Market Drivers
  • 3.3 Market Restraints and Challenges
  • 3.4 Growth Opportunities and Investment Hotspots
  • 3.5 Industry Threats and Risk Assessment
  • 3.6 Technology and Innovation Landscape
  • 3.7 Emerging and High-Growth Markets
  • 3.8 Regulatory and Policy Environment
  • 3.9 Impact of COVID-19 and Recovery Outlook

4 Competitive and Strategic Assessment

  • 4.1 Porter's Five Forces Analysis
    • 4.1.1 Supplier Bargaining Power
    • 4.1.2 Buyer Bargaining Power
    • 4.1.3 Threat of Substitutes
    • 4.1.4 Threat of New Entrants
    • 4.1.5 Competitive Rivalry
  • 4.2 Market Share Analysis of Key Players
  • 4.3 Product Benchmarking and Performance Comparison

5 Global Autonomous Material Handling Market, By Material Handling Type

  • 5.1 Autonomous Mobile Robots
  • 5.2 Automated Guided Vehicles
  • 5.3 Autonomous Forklifts
  • 5.4 Robotic Arms
  • 5.5 Autonomous Conveyors
  • 5.6 Other Material Handling Types

6 Global Autonomous Material Handling Market, By Navigation Technology

  • 6.1 LiDAR-Based Navigation
  • 6.2 Vision-Based Navigation
  • 6.3 Magnetic Navigation
  • 6.4 Reflector-Based Navigation
  • 6.5 SLAM-Based Navigation
  • 6.6 Other Navigation Technologies

7 Global Autonomous Material Handling Market, By Component

  • 7.1 Hardware
  • 7.2 Software
  • 7.3 Sensors
  • 7.4 Control Systems
  • 7.5 Communication Systems
  • 7.6 Other Components

8 Global Autonomous Material Handling Market, By Operation

  • 8.1 Picking
  • 8.2 Transporting
  • 8.3 Sorting
  • 8.4 Loading & Unloading
  • 8.5 Storage & Retrieval
  • 8.6 Other Operations

9 Global Autonomous Material Handling Market, By End User

  • 9.1 Manufacturing
  • 9.2 Retail & E-Commerce
  • 9.3 Food & Beverage
  • 9.4 Pharmaceuticals
  • 9.5 Logistics & Warehousing
  • 9.6 Other End Users

10 Global Autonomous Material Handling Market, By Geography

  • 10.1 North America
    • 10.1.1 United States
    • 10.1.2 Canada
    • 10.1.3 Mexico
  • 10.2 Europe
    • 10.2.1 United Kingdom
    • 10.2.2 Germany
    • 10.2.3 France
    • 10.2.4 Italy
    • 10.2.5 Spain
    • 10.2.6 Netherlands
    • 10.2.7 Belgium
    • 10.2.8 Sweden
    • 10.2.9 Switzerland
    • 10.2.10 Poland
    • 10.2.11 Rest of Europe
  • 10.3 Asia Pacific
    • 10.3.1 China
    • 10.3.2 Japan
    • 10.3.3 India
    • 10.3.4 South Korea
    • 10.3.5 Australia
    • 10.3.6 Indonesia
    • 10.3.7 Thailand
    • 10.3.8 Malaysia
    • 10.3.9 Singapore
    • 10.3.10 Vietnam
    • 10.3.11 Rest of Asia Pacific
  • 10.4 South America
    • 10.4.1 Brazil
    • 10.4.2 Argentina
    • 10.4.3 Colombia
    • 10.4.4 Chile
    • 10.4.5 Peru
    • 10.4.6 Rest of South America
  • 10.5 Rest of the World (RoW)
    • 10.5.1 Middle East
      • 10.5.1.1 Saudi Arabia
      • 10.5.1.2 United Arab Emirates
      • 10.5.1.3 Qatar
      • 10.5.1.4 Israel
      • 10.5.1.5 Rest of Middle East
    • 10.5.2 Africa
      • 10.5.2.1 South Africa
      • 10.5.2.2 Egypt
      • 10.5.2.3 Morocco
      • 10.5.2.4 Rest of Africa

11 Strategic Market Intelligence

  • 11.1 Industry Value Network and Supply Chain Assessment
  • 11.2 White-Space and Opportunity Mapping
  • 11.3 Product Evolution and Market Life Cycle Analysis
  • 11.4 Channel, Distributor, and Go-to-Market Assessment

12 Industry Developments and Strategic Initiatives

  • 12.1 Mergers and Acquisitions
  • 12.2 Partnerships, Alliances, and Joint Ventures
  • 12.3 New Product Launches and Certifications
  • 12.4 Capacity Expansion and Investments
  • 12.5 Other Strategic Initiatives

13 Company Profiles

  • 13.1 Daifuku Co., Ltd.
  • 13.2 Dematic GmbH
  • 13.3 KION Group AG
  • 13.4 Jungheinrich AG
  • 13.5 Toyota Industries Corporation
  • 13.6 Honeywell International Inc.
  • 13.7 ABB Ltd.
  • 13.8 Siemens AG
  • 13.9 Ocado Group plc
  • 13.10 Geekplus Technology Co., Ltd.
  • 13.11 Locus Robotics Corporation
  • 13.12 Seegrid Corporation
  • 13.13 OTTO Motors
  • 13.14 Balyo
  • 13.15 Exotec

List of Tables

  • Table 1 Global Autonomous Material Handling Market Outlook, By Region (2023-2034) ($MN)
  • Table 2 Global Autonomous Material Handling Market, By Material Handling Type (2023-2034) ($MN)
  • Table 3 Global Autonomous Material Handling Market, By Autonomous Mobile Robots (2023-2034) ($MN)
  • Table 4 Global Autonomous Material Handling Market, By Automated Guided Vehicles (2023-2034) ($MN)
  • Table 5 Global Autonomous Material Handling Market, By Autonomous Forklifts (2023-2034) ($MN)
  • Table 6 Global Autonomous Material Handling Market, By Robotic Arms (2023-2034) ($MN)
  • Table 7 Global Autonomous Material Handling Market, By Autonomous Conveyors (2023-2034) ($MN)
  • Table 8 Global Autonomous Material Handling Market, By Other Material Handling Types (2023-2034) ($MN)
  • Table 9 Global Autonomous Material Handling Market, By Navigation Technology (2023-2034) ($MN)
  • Table 10 Global Autonomous Material Handling Market, By LiDAR-Based Navigation (2023-2034) ($MN)
  • Table 11 Global Autonomous Material Handling Market, By Vision-Based Navigation (2023-2034) ($MN)
  • Table 12 Global Autonomous Material Handling Market, By Magnetic Navigation (2023-2034) ($MN)
  • Table 13 Global Autonomous Material Handling Market, By Reflector-Based Navigation (2023-2034) ($MN)
  • Table 14 Global Autonomous Material Handling Market, By SLAM-Based Navigation (2023-2034) ($MN)
  • Table 15 Global Autonomous Material Handling Market, By Other Navigation Technologies (2023-2034) ($MN)
  • Table 16 Global Autonomous Material Handling Market, By Component (2023-2034) ($MN)
  • Table 17 Global Autonomous Material Handling Market, By Hardware (2023-2034) ($MN)
  • Table 18 Global Autonomous Material Handling Market, By Software (2023-2034) ($MN)
  • Table 19 Global Autonomous Material Handling Market, By Sensors (2023-2034) ($MN)
  • Table 20 Global Autonomous Material Handling Market, By Control Systems (2023-2034) ($MN)
  • Table 21 Global Autonomous Material Handling Market, By Communication Systems (2023-2034) ($MN)
  • Table 22 Global Autonomous Material Handling Market, By Other Components (2023-2034) ($MN)
  • Table 23 Global Autonomous Material Handling Market, By Operation (2023-2034) ($MN)
  • Table 24 Global Autonomous Material Handling Market, By Picking (2023-2034) ($MN)
  • Table 25 Global Autonomous Material Handling Market, By Transporting (2023-2034) ($MN)
  • Table 26 Global Autonomous Material Handling Market, By Sorting (2023-2034) ($MN)
  • Table 27 Global Autonomous Material Handling Market, By Loading & Unloading (2023-2034) ($MN)
  • Table 28 Global Autonomous Material Handling Market, By Storage & Retrieval (2023-2034) ($MN)
  • Table 29 Global Autonomous Material Handling Market, By Other Operations (2023-2034) ($MN)
  • Table 30 Global Autonomous Material Handling Market, By End User (2023-2034) ($MN)
  • Table 31 Global Autonomous Material Handling Market, By Manufacturing (2023-2034) ($MN)
  • Table 32 Global Autonomous Material Handling Market, By Retail & E-Commerce (2023-2034) ($MN)
  • Table 33 Global Autonomous Material Handling Market, By Food & Beverage (2023-2034) ($MN)
  • Table 34 Global Autonomous Material Handling Market, By Pharmaceuticals (2023-2034) ($MN)
  • Table 35 Global Autonomous Material Handling Market, By Logistics & Warehousing (2023-2034) ($MN)
  • Table 36 Global Autonomous Material Handling Market, By Other End Users (2023-2034) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Rest of the World (RoW) are also represented in the same manner as above.