NebulaVLA: A Dual-Frequency Vision-Language-Action Model With Guide Action for Robotic Manipulation

2026-08-17

AI Summary

This study addresses critical bottlenecks in Vision-Language-Action (VLA) model deployment, including the efficiency-performance trade-off, limited cross-embodiment generalization, and jerky motion generation. To overcome these challenges, we propose an asynchronous dual-frequency architecture that decouples semantic reasoning from action control. Furthermore, we introduce GESTURE-7, a unified action representation, alongside a mask-guided smoothing constraint algorithm. Experimental evaluations on the LIBERO-Plus benchmark demonstrate that our method achieves an average success rate of 85.5% and accelerates action generation by approximately 2.7× compared to synchronous baselines. These results confirm that the proposed framework effectively enables efficient, smooth, and generalizable robotic manipulation, significantly outperforming existing approaches in both computational efficiency and operational robustness.

Abstract

Real-world deployment of Vision-Language-Action (VLA) models is often bottlenecked by efficiency-performance trade-offs, cross-embodiment generalization, and execution smoothness. We present NebulaVLA, an asynchronous dual-frequency architecture that decouples high-level semantic reasoning from low-level action control, optimizing computational resources and modularity. To bridge semantic gaps across heterogeneous robots, we introduce GESTURE-7, a unified language-grounded action representation. Furthermore, our Guide Action algorithm enforces kinematic continuity via mask-based smoothness constraints. Comprehensive evaluations demonstrate that NebulaVLA significantly outperforms synchronous baselines, achieving an 85.5\% average success rate on LIBERO-Plus and accelerating action generation by \textasciitilde 2.7$\times$. This asynchronous design enables highly efficient and responsive control for practical robotics.

Problem

• Vision-Language-Action
• Robotic Manipulation
• Cross-embodiment Generalization
• Execution Smoothness
• Efficiency-performance Trade-offs

Innovation

• Asynchronous Dual-Frequency Architecture
• GESTURE-7
• Guide Action
• Vision-Language-Action Model
• Cross-Embodiment Generalization