Abstract
Vision-Language-Action (VLA) models have achieved impressive results in robotic manipulation and ground-mobile navigation, yet language-conditioned control of unmanned aerial vehicles (UAVs) in smart warehouses remains largely unexplored, hindered by the lack of benchmarks that jointly provide continuous low-level flight actions, fine-grained natural-language target descriptions, and realistic industrial environments. This paper introduces WareFly-VLA, a photorealistic UAV VLA framework and dataset for language-guided human search, localization, and tracking in warehouse environments. It contains 507 human-teleoperated flight episodes and 8,504 high-resolution RGB transitions collected in NVIDIA Isaac Sim, each paired with a human-written appearance description of the target worker and a synchronized four-degree-of-freedom control command. Two aerial tasks are covered: target approach and person following, under occlusion, long-range search, altitude variation, and clutter. A unified benchmark of four open-source VLA architectures (SmolVLA, GR00T N1.7, pi_0 and OpenVLA) is established under a leakage-free episode-level protocol at two control rates. The results show that language-conditioned aerial control in warehouses is far from solved: performance drops substantially under strict generalization settings, continuous action modeling consistently outperforms discrete action tokenization, only the forward channel is reliably learnable from a single frame, and current foundation-model interfaces transfer poorly from ground and humanoid embodiments to aerial platforms. The synchronized video, language, action, pose, and difficulty annotations further support world-model research. The dataset, baselines, and evaluation protocol are released to support language-grounded aerial autonomy in smart warehouses.
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Publication details
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- Open access
- Green open access
Cite this article
APA 7
Le, T. D., Nguyen, S. T., Nguyen, D. Q., Le, D. D., Vien, N. A., & Nguyen-Xuan, H. (2026). WareFly-VLA: A Vision-Language-Action Framework for UAV Navigation and Human Tracking in Smart Warehouses. https://omanscience.com/en/articles/warefly-vla-a-vision-language-action-framework-for-uav-navigation-and-human-tracking-in-smart-warehouses
MLA 9
Le, Thinh D., et al. "WareFly-VLA: A Vision-Language-Action Framework for UAV Navigation and Human Tracking in Smart Warehouses." https://omanscience.com/en/articles/warefly-vla-a-vision-language-action-framework-for-uav-navigation-and-human-tracking-in-smart-warehouses.
Chicago (author–date)
Le, Thinh D., Son T. Nguyen, Duong Q. Nguyen, Dung D. Le, Ngo Anh Vien, and H. Nguyen-Xuan. 2026. "WareFly-VLA: A Vision-Language-Action Framework for UAV Navigation and Human Tracking in Smart Warehouses." https://omanscience.com/en/articles/warefly-vla-a-vision-language-action-framework-for-uav-navigation-and-human-tracking-in-smart-warehouses.
Harvard
Le, T. D., Nguyen, S. T., Nguyen, D. Q., Le, D. D., Vien, N. A. and Nguyen-Xuan, H. (2026) 'WareFly-VLA: A Vision-Language-Action Framework for UAV Navigation and Human Tracking in Smart Warehouses', Available at: https://omanscience.com/en/articles/warefly-vla-a-vision-language-action-framework-for-uav-navigation-and-human-tracking-in-smart-warehouses.
Vancouver
Le TD, Nguyen ST, Nguyen DQ, Le DD, Vien NA, Nguyen-Xuan H. WareFly-VLA: A Vision-Language-Action Framework for UAV Navigation and Human Tracking in Smart Warehouses. https://omanscience.com/en/articles/warefly-vla-a-vision-language-action-framework-for-uav-navigation-and-human-tracking-in-smart-warehouses
IEEE
T. D. Le, S. T. Nguyen, D. Q. Nguyen, D. D. Le, N. A. Vien, and H. Nguyen-Xuan, "WareFly-VLA: A Vision-Language-Action Framework for UAV Navigation and Human Tracking in Smart Warehouses," https://omanscience.com/en/articles/warefly-vla-a-vision-language-action-framework-for-uav-navigation-and-human-tracking-in-smart-warehouses.