工業/協作機器人領域的人工智慧格局

本報告探索並分析了工業/協作機器人領域的人工智慧市場，描繪了人工智慧驅動機器人技術的成熟度，評估了人工智慧在機器人領域的市場規模，並比較了工業和協作領域的應用模式。

關鍵問題解答

• 哪些新興的人工智慧方法正在推動機器人研發？它們距離商業化還有多遠？
• 哪些供應商和合作夥伴關係將塑造人工智慧賦能機器人的未來？它們在工業應用和協作應用方面有何不同？
• 人工智慧在機器人領域的應用時間表是什麼？技能差距、整合複雜性和傳統基礎設施等挑戰將如何影響其應用？
• 就成熟度和價值交付而言，人工智慧在機器人領域的應用可能與其他賦能技術（例如，數位工具）相當。 它與其他產業（例如自動化平台和工業物聯網 (IIoT)）相比如何？

目錄

主要發現

主要預測

主要參與者與生態系

機器人領域人工智慧成熟度指數

機器人DPA軟體供應商

機器人視覺硬體供應商

機器人領域的智能體人工智慧

機器人基礎模型

世界模型

新SLAM

結論

Actionable Benefits:

• Gain a clear understanding of how Artificial Intelligence (AI) is shaping robotics Research and Development (R&D), commercial maturity, and deployment strategies.
• Identify the most critical opportunities and risks in adopting AI-driven robotics across manufacturing, operations, and industrial settings.
• Benchmark vendor ecosystems, strategic partnerships, and competitive positioning to inform partnership and procurement strategies.
• Understand Total Addressable Market (TAM) dynamics for AI in robotics across Operational Technology (OT) and Information Technology (IT) domains, and how to align investment priorities accordingly.

Critical Questions Answered:

• What emerging AI methodologies are advancing robotics R&D, and how close are they to commercial readiness?
• Which vendors and partnerships are defining the future of AI-enabled robotics, and how do they differ across industrial and collaborative applications?
• What are the adoption timelines for AI in robotics, and how do challenges such as skills gaps, integration complexity, and legacy infrastructure affect uptake?
• How does AI in robotics compare with other enabling technologies (e.g., digital twins, automation platforms, and Industrial Internet of Things (IIoT)) in terms of maturity and value delivery?

Research Highlights:

• Mapping of AI-driven robotics maturity, from cutting-edge research methodologies to commercially deployed solutions.
• Analysis of vendor ecosystems, partnerships, and technology enablers shaping adoption pathways.
• TAM assessment for AI in robotics, segmented by OT and IT approaches.
• Insights into collaborative versus industrial robotics adoption patterns, with AI as the differentiator in productivity, flexibility, and safety outcomes.

Who Should Read This?

• C-level executives and strategy leaders in manufacturing, logistics, and industrial organizations evaluating robotics investment and AI integration.
• Product managers and R&D leaders at robotics, AI, and automation technology suppliers seeking quantitative support for roadmaps and partnerships.
• Innovation and digital transformation leaders exploring the intersection of AI, robotics, and Industry 4.0/5.0 technologies.
• Investors and market analysts assessing the growth potential, TAM, and maturity of AI in robotics across industrial ecosystems.

TABLE OF CONTENTS

Key Findings

Key Forecasts

Key Companies and Ecosystems

Maturity Index AI in Robotics

Robotics DPA Software Vendors

Robotics Vision Hardware Vendors

Agentic AI in Robotics

Robotics Foundation Models

World Models

The New SLAM

Final Thoughts