AI-empowered intelligence in industrial robotics: technologies, challenges, and emerging trends

作者：Yifan Chen, Tao Ren, Hao Liu, Gang Jiang, Qingyou Liu, Yonghua Chen, Simon X. Yang · 发表于：Intelligence & Robotics · 年份：2026 · DOI：10.20517/ir.2026.01 · 被引用次数：5 · 研究领域：AI-based Problem Solving and Planning、Robot Manipulation and Learning、Flexible and Reconfigurable Manufacturing Systems

Artificial intelligence (AI) is profoundly reshaping the technological framework of industrial robotics, driving its transition from pre-programmed automation to autonomous, adaptive agents. This paper systematically reviews the key advancements of AI across three core dimensions of intelligence: perception, decision-making, and execution. Analysis indicates that AI is propelling industrial robots from tools executing predefined tasks towards intelligent partners capable of adapting to unstructured environments, autonomously planning amid dynamic changes, and engaging in nuanced interactions with the physical world. This evolution reveals a shift from optimizing specific skills towards developing rudimentary task-level cognitive reasoning capabilities. Nevertheless, fundamental challenges persist for industrial-scale deployment, including model generalization capabilities, long-term robustness, and human-machine trust. Collectively, these advancements are shaping a new generation of intelligent industrial robotic systems that are more adaptable and capable of deeper collaboration with humans.