Vision–Language–Action Models for Agricultural Robotics: A Review Towards Embodied Intelligence

Xiaopei Yang; Jie He; Lei Ye; Zhaojie Wu; Yunchao Tang; Xiwen Luo

doi:10.1016/j.eng.2026.06.021

Engineering ›› :202606021 DOI: 10.1016/j.eng.2026.06.021

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Vision–Language–Action Models for Agricultural Robotics: A Review Towards Embodied Intelligence

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Abstract

The shift toward Agriculture 5.0 demands robotic systems that can reason and act reliably in unstructured, high-entropy environments. Conventional agricultural robots, limited by rigid modular pipelines, often fail to generalize across diverse crop morphologies and rapidly changing field conditions. In contrast to existing surveys on general-purpose robotics, this paper provides a comprehensive review of vision–language–action (VLA) collaborative intelligence systems. It proposes a transformative framework that integrates multimodal foundation models to bridge the cognitive gap in agricultural robotics. We systematically examine VLA architectures along three core dimensions tailored to agricultural

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Agricultural robotics / Vision–language–action models / Embodied intelligence / Large language models / Precision agriculture

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Xiaopei Yang, Jie He, Lei Ye, Zhaojie Wu, Yunchao Tang, Xiwen Luo. Vision–Language–Action Models for Agricultural Robotics: A Review Towards Embodied Intelligence. Engineering 202606021 DOI:10.1016/j.eng.2026.06.021

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