工业/协作机器人领域的人工智慧格局

本报告探索并分析了工业/协作机器人领域的人工智慧市场，描绘了人工智慧驱动机器人技术的成熟度，评估了人工智慧在机器人领域的市场规模，并比较了工业和协作领域的应用模式。

关键问题解答

• 哪些新兴的人工智慧方法正在推动机器人研发？它们距离商业化还有多远？
• 哪些供应商和合作伙伴关係将塑造人工智慧赋能机器人的未来？它们在工业应用和协作应用方面有何不同？
• 人工智慧在机器人领域的应用时间表是什么？技能差距、整合复杂性和传统基础设施等挑战将如何影响其应用？
• 就成熟度和价值交付而言，人工智慧在机器人领域的应用可能与其他赋能技术（例如，数位工具）相当。 它与其他产业（例如自动化平台和工业物联网 (IIoT)）相比如何？

目录

主要发现

主要预测

主要参与者与生态系

机器人领域人工智慧成熟度指数

机器人DPA软体供应商

机器人视觉硬体供应商

机器人领域的智能体人工智慧

机器人基础模型

世界模型

新SLAM

结论

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