Survey of Vision-Language-Action Models for Embodied Manipulation

Embodied intelligence systems, which enhance agent capabilities through continuous environment interactions, have garnered significant attention from both academia and industry. Vision-language-action (VLA) 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 intelligence robots. This survey comprehensively reviews VLA models for embodied manipulation. Firstly, it introduces the developmental history of VLA models. Subsequently, it conducts a detailed analysis of current research status across 5 critical dimensions: VLA model structures, training datasets, pre-training methods, post-training methods, and model evaluation. Finally, it summarizes key challenges in VLA model development and real-world deployment, while outlining promising future development directions.