Survey of Vision-Language-Action Models for Embodied Manipulation

• URL: http://arxiv.org/abs/2508.15201v1
• Date: Thu, 21 Aug 2025 03:30:04 GMT
• Title: Survey of Vision-Language-Action Models for Embodied Manipulation
• Authors: Haoran Li, Yuhui Chen, Wenbo Cui, Weiheng Liu, Kai Liu, Mingcai Zhou, Zhengtao Zhang, Dongbin Zhao,
• Abstract summary: Embodied intelligence systems enhance agent capabilities through continuous environment interactions.<n>Vision-Language-Action models, inspired by advancements in large foundation models, serve as universal robotic control frameworks.<n>This survey comprehensively reviews VLA models for embodied manipulation.
• Score: 12.586030711502858
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Embodied intelligence systems, which enhance agent capabilities through continuous environment interactions, have garnered significant attention from both academia and industry. Vision-Language-Action models, inspired by advancements in large foundation models, serve as universal robotic control frameworks that substantially improve agent-environment interaction capabilities in embodied intelligence systems. This expansion has broadened application scenarios for embodied AI robots. This survey comprehensively reviews VLA models for embodied manipulation. Firstly, it chronicles the developmental trajectory of VLA architectures. Subsequently, we conduct a detailed analysis of current research across 5 critical dimensions: VLA model structures, training datasets, pre-training methods, post-training methods, and model evaluation. Finally, we synthesize key challenges in VLA development and real-world deployment, while outlining promising future research directions.

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