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A Comprehensive Review and Future Perspectives on Embodied AI Large Models
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Tingyu YUAN1, 2, Kai LIU3, Biaoliang GUAN3, Wen YE2, 4, Yacui ZHAO5, Chaoyang ZHAO1, 6, Jinqiao WANG1, 2
Radio Engineering | 2025, 55(11) : 2256 - 2273
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Radio Engineering | 2025, 55(11): 2256-2273
Engineering & Application
A Comprehensive Review and Future Perspectives on Embodied AI Large Models
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Tingyu YUAN1, 2, Kai LIU3, Biaoliang GUAN3, Wen YE2, 4, Yacui ZHAO5, Chaoyang ZHAO1, 6, Jinqiao WANG1, 2
Affiliations
  • 1.Foundation Model Research Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100083, China
  • 2.School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100083, China
  • 3.School of Software Engineering, Xi’an Jiaotong University, Xi’an 710049, China
  • 4.New Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100083, China
  • 5.The Hamlyn Centre, Imperial College London, London SW7 2AZ , United Kingdom
  • 6.Objecteye. Inc, Beijing 100083, China
Published: 2025-11-05 doi: 10.3969/j.issn.1003-3106.2025.11.014
Outline
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Vision-Language-Action (VLA) models are a core technology for achieving general embodied artificial intelligence, aiming to integrate visual perception, language understanding, and action decision-making within a unified end-to-end framework. The current research status and development trajectory of VLA models are comprehensively and systematically reviewed. The theoretical origins of VLA models are traced, and the paradigm shift from modular designs to unified architectures is clarified. Along the evolutionary path of VLA, representative works such as SpatialVLA, TLA, and GR00T N1 are presented with a focus on multimodal fusion and cognitive hierarchies. A detailed taxonomy of VLA models is constructed from two key dimensions-macro architecture and system hierarchy. Key technologies and design principles are deeply analyzed, ranging from pioneering works such as RT-1, to models introducing large-scale knowledge transfer such as RT-2, OpenVLA, and ECOT, and further to cutting-edge dual-system architectures such as Helix, OpenHelix, DexVLA, and DexGraspVLA. Mainstream simulation environments, core datasets, and benchmarks supporting VLA research are systematically integrated and reviewed. The application status and prospects of VLA models in robotic manipulation, autonomous navigation, and industrial automation are explored. Core challenges in current VLA research are analyzed, including generalization and data efficiency, long-horizon task planning, and real-time responsiveness. Future research directions are discussed, including integration with world models and enhancement of data efficiency.

VLA models  /  large models  /  embodied AI  /  robot learning  /  multimodal learning
Tingyu YUAN, Kai LIU, Biaoliang GUAN, Wen YE, Yacui ZHAO, Chaoyang ZHAO, Jinqiao WANG. A Comprehensive Review and Future Perspectives on Embodied AI Large Models[J]. Radio Engineering, 2025 , 55 (11) : 2256 -2273 . DOI: 10.3969/j.issn.1003-3106.2025.11.014
Year 2025 volume 55 Issue 11
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Article Info
doi: 10.3969/j.issn.1003-3106.2025.11.014
  • Receive Date:2025-08-02
  • Online Date:2026-04-17
  • Published:2025-11-05
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  • Received:2025-08-02
Affiliations
    1.Foundation Model Research Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100083, China
    2.School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100083, China
    3.School of Software Engineering, Xi’an Jiaotong University, Xi’an 710049, China
    4.New Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100083, China
    5.The Hamlyn Centre, Imperial College London, London SW7 2AZ , United Kingdom
    6.Objecteye. Inc, Beijing 100083, China
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小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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