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市場調查報告書
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1936180

自主移動機器人 (AMR) 市場規模、佔有率及預測：依感測器類型（雷射雷達、視覺、雷達、超音波）、感測器融合演算法、SLAM 技術及應用（倉庫、工廠、戶外）劃分 - 全球預測至 2036 年

Autonomous Mobile Robot (AMR) Market Size, Share, & Forecast by Sensor Type (Lidar, Vision, Radar, Ultrasonic), Sensor Fusion Algorithms, SLAM Technology, and Application (Warehouse, Factory, Outdoor) - Global Forecast to 2036
出版日期: | 出版商: Meticulous Research | 英文 275 Pages | 商品交期: 5-7個工作天內

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簡介目錄

預計 2026 年至 2036 年，全球自主移動機器人市場將以 19.3% 的複合年增長率成長，到 2036 年市場規模將達到 284.5 億美元。本報告對五大主要地區的自主移動機器人市場進行了詳細分析，重點關注當前市場趨勢、市場規模、近期發展以及至 2036 年的預測。基於廣泛的一手和二手研究以及對市場現狀的深入分析，本報告對關鍵產業驅動因素、限制因素、機會和挑戰進行了影響分析。該市場的成長受多種因素驅動，例如物料搬運自動化和營運效率提升的重要性、電子商務和物流配送的快速擴張、勞動力成本壓力和勞動力短缺、人工智慧導航和避障技術的進步，以及先進感測器融合和SLAM演算法的開發。此外，先進的雷射雷達、視覺和雷達感測器技術的整合、雲端車隊管理系統的採用、對工作場所安全和協作自動化的日益重視、能夠適應各種環境的戶外自主移動機器人（AMR）的開發，以及製造業和物流業對自主系統的日益普及，預計也將推動市場成長。

目錄

第一章：引言

第二章：研究方法

第三章：摘要整理

  • 依感測器類型劃分的市場分析
  • 依感測器融合演算法劃分的市場分析
  • 依SLAM技術劃分的市場分析
  • 依導航方式劃分的市場分析
  • 以貨物容量劃分的市場分析
  • 依應用劃分的市場分析
  • 依最終用戶產業劃分的市場分析
  • 依地區劃分的市場分析
  • 依競爭分析劃分的市場分析

第四章 市場洞察

  • 市場驅動因素
    • 電子商務的快速成長和對物流自動化的需求
    • 持續的勞動短缺和勞動成本的上升成本
    • 工業4.0和智慧製造的採用
  • 市場限制因素
    • 高額初始投資與整合複雜性
    • 基礎設施需求和營運限制
  • 市場機遇
    • 從倉庫管理擴展到生產車間和戶外應用（規模龐大）
    • 建構整合人工智慧和車隊管理的自動化平台
  • 市場挑戰
    • 安全認證與人機協作
    • 供應商標準化和互通性
  • 市場趨勢
    • 向智慧協作機器人群集演進
    • 採用機器人即服務 (RaaS) 商業模式
  • 波特五力模型分析

第五章 自主移動機器人 (AMR) 的導航技術與人工智慧演算法

  • 基於雷射雷達的感知與建圖
  • 基於視覺的導航與目標識別
  • 感測器融合與多模態感知
  • SLAM 演算法與定位技術
  • 路徑規劃與避障
  • 車隊管理與多機器人協作
  • 用於自適應行為的人工智慧和機器學習
  • 市場成長及其對技術採納的影響

第六章：競爭格局

  • 關鍵成長策略
    • 市場差異化因素
    • 協同效應分析：關鍵交易與策略聯盟
  • 競爭格局概覽
    • 行業領導者
    • 市場差異化因素
    • 先驅者
    • 新興公司
  • 供應商市場定位
  • 主要公司市佔率/排名

第七章 全球自主移動機器人 (AMR) 市場（依感測器類型劃分）

  • 光達感測器
    • 2D 光達
    • 3D 光達
  • 視覺相機
    • RGB 相機
    • 立體相機
    • 3D 相機（飛行時間、結構光）
  • 雷達感測器
  • 超音波感測器
  • 慣性測量單元 (IMU) 和里程計感測器

第八章 全球自主移動機器人 (AMR) 市場（依感測器融合演算法劃分）

  • 多模態融合
    • 基於卡爾曼濾波的融合
    • 基於粒子濾波的融合
    • 深度學習融合
  • 光達-相機融合
  • 光達-雷達融合
  • 視覺-慣性測量單元融合
  • 綜合多感測器融合

第九章 全球自主移動機器人（AMR）市場（基於SLAM技術）

  • 以雷射為基礎的SLAM
    • 2D SLAM
    • 3D SLAM
    • 基於圖的SLAM
  • 視覺SLAM（VSLAM）
    • 單目SLAM
    • 立體SLAM
    • RGB-D SLAM
  • 混合SLAM （多感測器）
  • 基於學習的SLAM

第十章 全球自主移動機器人（AMR）市場（以導航方式劃分）

  • 自然特徵導航
  • 反射器導航
  • 二維碼/標記導航
  • 混合導航
  • GPS導航（室外）

第十一章 全球自主移動機器人（AMR）市場（依酬載能力劃分）

  • 輕型酬載（100公斤以下）
  • 中型酬載（100-500公斤）
  • 重型酬載（500-1500公斤）
  • 超重型酬載（1500公斤以上）

第十二章 全球自主移動機器人（自主移動機器人）市場依應用領域劃分

  • 倉儲與物流
    • 人揀貨
    • 庫存移動與補貨
    • 分類與配送
    • 退貨處理
  • 製造與組裝
    • 物料運送至生產線
    • 在製品運輸
    • 套件組裝與零件配送
    • 成品運輸
  • 戶外及外送應用
    • 末端配送機器人
    • 自動場內運輸車
    • 農業與農場
  • 醫療保健與飯店
  • 巡檢與安防

第十三章 全球自主移動機器人（AMR）市場依最終用戶劃分產業

  • 電子商務與零售
  • 第三方物流 (3PL)
  • 汽車製造
  • 電子與高科技製造
  • 食品和飲料
  • 製藥和醫療保健
  • 航空航太與國防
  • 其他

第十四章 自主移動機器人 (AMR) 市場（依地區劃分）

  • 北美
    • 美國
    • 加拿大
  • 歐洲
    • 德國
    • 英國
    • 法國
    • 義大利
    • 西班牙
    • 瑞典
    • 歐洲其他地區
  • 亞太地區
    • 中國
    • 日本
    • 東南亞韓國
    • 印度
    • 澳大利亞
    • 東南亞
    • 亞太其他地區
  • 拉丁美洲
    • 巴西
    • 墨西哥
    • 阿根廷
    • 拉丁美洲其他地區
  • 中東和非洲
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 南非
    • 中東和非洲其他地區

第十五章 公司簡介

  • 移動工業機器人（MiR）
  • Fetch Robotics（斑馬技術）
  • Locus Robotics Corporation
  • GreyOrange Inc.
  • Geek+（北京極客科技股份有限公司）
  • AutoStore
  • Vecna Robotics
  • OTTO馬達（Clearpath Robotics）
  • 庫卡股份公司（Swisslog）
  • ABB有限公司
  • 歐姆龍株式會社（Adept Technology）
  • 西門子股份公司
  • HoneywellIntelligrated
  • 德馬泰克（凱傲集團）
  • 亞馬遜機器人
  • 波士頓動力公司
  • Seegrid公司
  • IAM Robotics
  • inVia Robotics
  • Agilox Services GmbH
  • 其他

第16章附錄

簡介目錄
Product Code: MRSE - 1041672

Autonomous Mobile Robot (AMR) Market by Sensor Type (Lidar, Vision, Radar, Ultrasonic), Sensor Fusion Algorithms, SLAM Technology, and Application (Warehouse, Factory, Outdoor) - Global Forecasts (2026-2036)

According to the research report titled, 'Autonomous Mobile Robot (AMR) Market by Sensor Type (Lidar, Vision, Radar, Ultrasonic), Sensor Fusion Algorithms, SLAM Technology, and Application (Warehouse, Factory, Outdoor) - Global Forecasts (2026-2036),' the autonomous mobile robot market is projected to reach USD 28.45 billion by 2036, at a CAGR of 19.3% during the forecast period 2026-2036. The report provides an in-depth analysis of the global autonomous mobile robot market across five major regions, emphasizing the current market trends, market sizes, recent developments, and forecasts till 2036. Following extensive secondary and primary research and an in-depth analysis of the market scenario, the report conducts the impact analysis of the key industry drivers, restraints, opportunities, and challenges. The growth of this market is driven by the critical need to automate material handling and improve operational efficiency, the rapid expansion of e-commerce and fulfillment operations, labor cost pressures and workforce shortages, the advancement of AI-powered navigation and obstacle avoidance technologies, and the development of sophisticated sensor fusion and SLAM algorithms. Moreover, the integration of advanced lidar, vision, and radar sensor technologies, the adoption of cloud-based fleet management systems, the increasing focus on workplace safety and collaborative automation, the development of outdoor-capable AMRs for diverse environments, and the growing adoption of autonomous systems across manufacturing and logistics sectors are expected to support the market's growth.

Key Players

The key players operating in the autonomous mobile robot market are Mobile Industrial Robots (MiR) (Denmark), Fetch Robotics/Zebra Technologies (U.S.), Locus Robotics Corporation (U.S.), GreyOrange Inc. (Singapore/India), Geek+ (China), AutoStore (Norway), Vecna Robotics (U.S.), OTTO Motors/Clearpath Robotics (Canada), KUKA AG/Swisslog (Germany), ABB Ltd. (Switzerland), OMRON Corporation/Adept Technology (Japan), Siemens AG (Germany), Honeywell Intelligrated (U.S.), Dematic/KION Group (Germany/U.S.), Amazon Robotics (U.S.), Boston Dynamics (U.S.), Seegrid Corporation (U.S.), IAM Robotics (U.S.), inVia Robotics (U.S.), and Agilox Services GmbH (Austria), among others.

Market Segmentation

The autonomous mobile robot market is segmented by sensor type (lidar, vision, radar, ultrasonic, and others), sensor fusion algorithms (probabilistic, deterministic, and hybrid), SLAM technology (visual SLAM, lidar-based SLAM, and hybrid SLAM), application (warehouse and fulfillment, factory and manufacturing, outdoor and delivery, and others), payload capacity (light-duty <100 kg, medium-duty 100-500 kg, heavy-duty >500 kg), and geography. The study also evaluates industry competitors and analyzes the market at the country level.

Based on Sensor Type

Based on sensor type, the lidar segment holds the largest market share in 2026. This segment's dominance is primarily attributed to superior accuracy for distance measurement and mapping, proven performance in diverse environments, and widespread adoption in commercial AMRs. The vision-based sensor segment is expected to grow at the highest CAGR during the forecast period, driven by advancements in computer vision algorithms, cost reduction in camera technology, and increasing adoption for visual navigation and obstacle recognition.

Based on Sensor Fusion Algorithms

Based on sensor fusion algorithms, the probabilistic fusion segment holds the largest market share in 2026. This segment's leadership is driven by proven effectiveness in combining multiple sensor inputs and reducing uncertainty in navigation. The hybrid fusion segment is expected to grow at the highest CAGR during the forecast period, driven by the need for robust and reliable navigation in complex and dynamic environments.

Based on SLAM Technology

Based on SLAM technology, the lidar-based SLAM segment holds the largest share of the overall market in 2026. This segment's dominance is driven by high accuracy and reliability for indoor navigation and mapping. The visual SLAM segment is expected to grow at a significant CAGR, driven by cost-effectiveness and compatibility with vision-based sensor systems. The hybrid SLAM segment is expected to witness substantial growth due to superior performance in diverse and challenging environments.

Based on Application

Based on application, the warehouse and fulfillment segment holds the largest share of the overall market in 2026. This segment's dominance is driven by extensive e-commerce growth and the need for rapid order fulfillment. The factory and manufacturing segment is expected to grow at a significant CAGR, driven by Industry 4.0 initiatives and the need for flexible automation. The outdoor and delivery segment is expected to witness the highest CAGR, driven by rapid expansion of last-mile delivery services and autonomous delivery platforms.

Geographic Analysis

An in-depth geographic analysis of the industry provides detailed qualitative and quantitative insights into the five major regions (North America, Europe, Asia-Pacific, Latin America, and the Middle East & Africa) and the coverage of major countries in each region. In 2026, North America is estimated to account for the largest share of the global autonomous mobile robot market, driven by early automation adoption, extensive warehouse and fulfillment operations, labor cost pressures, and strong presence of AMR vendors and end-users. Asia-Pacific is projected to register the highest CAGR during the forecast period, fueled by rapid manufacturing expansion, massive e-commerce growth, government automation initiatives, and cost-competitive AMR manufacturing ecosystem. The region's rapid industrial transformation is creating substantial market opportunities.

Key Questions Answered in the Report-

  • What is the current revenue generated by the autonomous mobile robot market globally?
  • At what rate is the global autonomous mobile robot demand projected to grow for the next 7-10 years?
  • What are the historical market sizes and growth rates of the global autonomous mobile robot market?
  • What are the major factors impacting the growth of this market at the regional and country levels? What are the major opportunities for existing players and new entrants in the market?
  • Which segments in terms of sensor type, sensor fusion algorithms, SLAM technology, and application are expected to create major traction for the manufacturers in this market?
  • What are the key geographical trends in this market? Which regions/countries are expected to offer significant growth opportunities for the companies operating in the global autonomous mobile robot market?
  • Who are the major players in the global autonomous mobile robot market? What are their specific product offerings in this market?
  • What are the recent strategic developments in the global autonomous mobile robot market? What are the impacts of these strategic developments on the market?

Scope of the Report:

Autonomous Mobile Robot Market Assessment -- by Sensor Type

  • Lidar
  • Vision
  • Radar
  • Ultrasonic
  • Other Sensor Types

Autonomous Mobile Robot Market Assessment -- by Sensor Fusion Algorithms

  • Probabilistic
  • Deterministic
  • Hybrid

Autonomous Mobile Robot Market Assessment -- by SLAM Technology

  • Visual SLAM
  • Lidar-Based SLAM
  • Hybrid SLAM

Autonomous Mobile Robot Market Assessment -- by Application

  • Warehouse and Fulfillment
  • Factory and Manufacturing
  • Outdoor and Delivery
  • Other Applications

Autonomous Mobile Robot Market Assessment -- by Payload Capacity

  • Light-Duty (<100 kg)
  • Medium-Duty (100-500 kg)
  • Heavy-Duty (>500 kg)

Autonomous Mobile Robot Market Assessment -- by Geography

  • North America
  • U.S.
  • Canada
  • Europe
  • Germany
  • U.K.
  • France
  • Spain
  • Italy
  • Rest of Europe
  • Asia-Pacific
  • China
  • India
  • Japan
  • South Korea
  • Australia & New Zealand
  • Rest of Asia-Pacific
  • Latin America
  • Mexico
  • Brazil
  • Argentina
  • Rest of Latin America
  • Middle East & Africa
  • Saudi Arabia
  • UAE
  • South Africa
  • Rest of Middle East & Africa

TABLE OF CONTENTS

1. Introduction

  • 1.1. Market Definition
  • 1.2. Market Ecosystem
  • 1.3. Currency and Limitations
    • 1.3.1. Currency
    • 1.3.2. Limitations
  • 1.4. Key Stakeholders

2. Research Methodology

  • 2.1. Research Approach
  • 2.2. Data Collection & Validation
    • 2.2.1. Secondary Research
    • 2.2.2. Primary Research
  • 2.3. Market Assessment
    • 2.3.1. Market Size Estimation
    • 2.3.2. Bottom-Up Approach
    • 2.3.3. Top-Down Approach
    • 2.3.4. Growth Forecast
  • 2.4. Assumptions for the Study

3. Executive Summary

  • 3.1. Overview
  • 3.2. Market Analysis, by Sensor Type
  • 3.3. Market Analysis, by Sensor Fusion Algorithm
  • 3.4. Market Analysis, by SLAM Technology
  • 3.5. Market Analysis, by Navigation Method
  • 3.6. Market Analysis, by Payload Capacity
  • 3.7. Market Analysis, by Application
  • 3.8. Market Analysis, by End-User Industry
  • 3.9. Market Analysis, by Geography
  • 3.10. Competitive Analysis

4. Market Insights

  • 4.1. Introduction
  • 4.2. Global Autonomous Mobile Robot (AMR) Market: Impact Analysis of Market Drivers (2026-2036)
    • 4.2.1. Explosive E-Commerce Growth and Fulfillment Automation Demands
    • 4.2.2. Persistent Labor Shortages and Rising Labor Costs
    • 4.2.3. Industry 4.0 and Smart Manufacturing Adoption
  • 4.3. Global Autonomous Mobile Robot (AMR) Market: Impact Analysis of Market Restraints (2026-2036)
    • 4.3.1. High Initial Investment and Integration Complexity
    • 4.3.2. Infrastructure Requirements and Operational Constraints
  • 4.4. Global Autonomous Mobile Robot (AMR) Market: Impact Analysis of Market Opportunities (2026-2036)
    • 4.4.1. Expansion Beyond Warehousing into Manufacturing and Outdoor Applications
    • 4.4.2. Integration with AI and Fleet Management Creating Automation Platforms
  • 4.5. Global Autonomous Mobile Robot (AMR) Market: Impact Analysis of Market Challenges (2026-2036)
    • 4.5.1. Safety Certification and Human-Robot Collaboration
    • 4.5.2. Standardization and Interoperability Across Vendors
  • 4.6. Global Autonomous Mobile Robot (AMR) Market: Impact Analysis of Market Trends (2026-2036)
    • 4.6.1. Evolution Toward Intelligent Collaborative Robot Fleets
    • 4.6.2. Robot-as-a-Service (RaaS) Business Model Adoption
  • 4.7. Porter's Five Forces Analysis
    • 4.7.1. Threat of New Entrants
    • 4.7.2. Bargaining Power of Suppliers
    • 4.7.3. Bargaining Power of Buyers
    • 4.7.4. Threat of Substitute Products
    • 4.7.5. Competitive Rivalry

5. Navigation Technologies and AI Algorithms for AMRs

  • 5.1. Introduction to AMR Navigation Technologies
  • 5.2. Lidar-Based Perception and Mapping
  • 5.3. Vision-Based Navigation and Object Recognition
  • 5.4. Sensor Fusion and Multi-Modal Perception
  • 5.5. SLAM Algorithms and Localization Techniques
  • 5.6. Path Planning and Obstacle Avoidance
  • 5.7. Fleet Management and Multi-Robot Coordination
  • 5.8. AI and Machine Learning for Adaptive Behaviors
  • 5.9. Impact on Market Growth and Technology Adoption

6. Competitive Landscape

  • 6.1. Introduction
  • 6.2. Key Growth Strategies
    • 6.2.1. Market Differentiators
    • 6.2.2. Synergy Analysis: Major Deals & Strategic Alliances
  • 6.3. Competitive Dashboard
    • 6.3.1. Industry Leaders
    • 6.3.2. Market Differentiators
    • 6.3.3. Vanguards
    • 6.3.4. Emerging Companies
  • 6.4. Vendor Market Positioning
  • 6.5. Market Share/Ranking by Key Players

7. Global Autonomous Mobile Robot (AMR) Market, by Sensor Type

  • 7.1. Introduction
  • 7.2. Lidar Sensors
    • 7.2.1. 2D Lidar
    • 7.2.2. 3D Lidar
  • 7.3. Vision Cameras
    • 7.3.1. RGB Cameras
    • 7.3.2. Stereo Cameras
    • 7.3.3. 3D Cameras (ToF, Structured Light)
  • 7.4. Radar Sensors
  • 7.5. Ultrasonic Sensors
  • 7.6. IMU and Odometry Sensors

8. Global Autonomous Mobile Robot (AMR) Market, by Sensor Fusion Algorithm

  • 8.1. Introduction
  • 8.2. Multi-Modal Fusion
    • 8.2.1. Kalman Filter-Based Fusion
    • 8.2.2. Particle Filter-Based Fusion
    • 8.2.3. Deep Learning Fusion
  • 8.3. Lidar-Camera Fusion
  • 8.4. Lidar-Radar Fusion
  • 8.5. Vision-IMU Fusion
  • 8.6. Comprehensive Multi-Sensor Fusion

9. Global Autonomous Mobile Robot (AMR) Market, by SLAM Technology

  • 9.1. Introduction
  • 9.2. Laser-Based SLAM
    • 9.2.1. 2D SLAM
    • 9.2.2. 3D SLAM
    • 9.2.3. Graph-Based SLAM
  • 9.3. Visual SLAM (VSLAM)
    • 9.3.1. Monocular SLAM
    • 9.3.2. Stereo SLAM
    • 9.3.3. RGB-D SLAM
  • 9.4. Hybrid SLAM (Multi-Sensor)
  • 9.5. Learning-Based SLAM

10. Global Autonomous Mobile Robot (AMR) Market, by Navigation Method

  • 10.1. Introduction
  • 10.2. Natural Feature Navigation
  • 10.3. Reflector-Based Navigation
  • 10.4. QR Code/Marker Navigation
  • 10.5. Hybrid Navigation
  • 10.6. GPS-Based Navigation (Outdoor)

11. Global Autonomous Mobile Robot (AMR) Market, by Payload Capacity

  • 11.1. Introduction
  • 11.2. Light Payload (Up to 100 kg)
  • 11.3. Medium Payload (100-500 kg)
  • 11.4. Heavy Payload (500-1500 kg)
  • 11.5. Extra Heavy Payload (Above 1500 kg)

12. Global Autonomous Mobile Robot (AMR) Market, by Application

  • 12.1. Introduction
  • 12.2. Warehouse and Logistics
    • 12.2.1. Goods-to-Person Picking
    • 12.2.2. Inventory Movement and Replenishment
    • 12.2.3. Sorting and Distribution
    • 12.2.4. Returns Processing
  • 12.3. Manufacturing and Assembly
    • 12.3.1. Material Delivery to Production Lines
    • 12.3.2. Work-in-Process Transport
    • 12.3.3. Kitting and Component Delivery
    • 12.3.4. Finished Goods Transport
  • 12.4. Outdoor and Delivery Applications
    • 12.4.1. Last-Mile Delivery Robots
    • 12.4.2. Autonomous Yard Trucks
    • 12.4.3. Agriculture and Farming
  • 12.5. Healthcare and Hospitality
  • 12.6. Inspection and Security

13. Global Autonomous Mobile Robot (AMR) Market, by End-User Industry

  • 13.1. Introduction
  • 13.2. E-Commerce and Retail
  • 13.3. Third-Party Logistics (3PL)
  • 13.4. Automotive Manufacturing
  • 13.5. Electronics and High-Tech Manufacturing
  • 13.6. Food and Beverage
  • 13.7. Pharmaceuticals and Healthcare
  • 13.8. Aerospace and Defense
  • 13.9. Others

14. Autonomous Mobile Robot (AMR) Market, by Geography

  • 14.1. Introduction
  • 14.2. North America
    • 14.2.1. U.S.
    • 14.2.2. Canada
  • 14.3. Europe
    • 14.3.1. Germany
    • 14.3.2. U.K.
    • 14.3.3. France
    • 14.3.4. Italy
    • 14.3.5. Spain
    • 14.3.6. Sweden
    • 14.3.7. Rest of Europe
  • 14.4. Asia-Pacific
    • 14.4.1. China
    • 14.4.2. Japan
    • 14.4.3. South Korea
    • 14.4.4. India
    • 14.4.5. Australia
    • 14.4.6. Southeast Asia
    • 14.4.7. Rest of Asia-Pacific
  • 14.5. Latin America
    • 14.5.1. Brazil
    • 14.5.2. Mexico
    • 14.5.3. Argentina
    • 14.5.4. Rest of Latin America
  • 14.6. Middle East & Africa
    • 14.6.1. Saudi Arabia
    • 14.6.2. UAE
    • 14.6.3. South Africa
    • 14.6.4. Rest of Middle East & Africa

15. Company Profiles

  • 15.1. Mobile Industrial Robots (MiR)
  • 15.2. Fetch Robotics (Zebra Technologies)
  • 15.3. Locus Robotics Corporation
  • 15.4. GreyOrange Inc.
  • 15.5. Geek+ (Beijing Geekplus Technology Co. Ltd.)
  • 15.6. AutoStore
  • 15.7. Vecna Robotics
  • 15.8. OTTO Motors (Clearpath Robotics)
  • 15.9. KUKA AG (Swisslog)
  • 15.10. ABB Ltd.
  • 15.11. OMRON Corporation (Adept Technology)
  • 15.12. Siemens AG
  • 15.13. Honeywell Intelligrated
  • 15.14. Dematic (KION Group)
  • 15.15. Amazon Robotics
  • 15.16. Boston Dynamics
  • 15.17. Seegrid Corporation
  • 15.18. IAM Robotics
  • 15.19. inVia Robotics
  • 15.20. Agilox Services GmbH
  • 15.21. Others

16. Appendix

  • 16.1. Questionnaire
  • 16.2. Available Customization