7 papers
Action with Visual Primitives
Weilong Guo, Yuchen Wang, Renping Zhou +5
Vision-Language-Action (VLA) models have emerged as a promising paradigm for generalist robotic manipulation. A common design in current architectures maps language instructions an…
WorldFly: A World-Model-Based Vision-Language-Action Model for UAV Navigation
Shengtao Zheng, Kai Li, Weichen Zhang +5
End-to-end Vision-Language-Action (VLA) models have shown promise in UAV navigation. However, existing approaches typically rely on historical observations to directly predict acti…
TGPO: Temporal Grounded Policy Optimization for Signal Temporal Logic Tasks
Yue Meng, Fei Chen, Chuchu Fan
Learning control policies for complex, long-horizon tasks is a central challenge in robotics and autonomous systems. Signal Temporal Logic (STL) offers a powerful and expressive la…
AuDeRe: Automated Strategy Decision and Realization in Robot Planning and Control via LLMs
Yue Meng, Fei Chen, Yongchao Chen +1
Recent advancements in large language models (LLMs) have shown significant promise in various domains, especially robotics. However, most prior LLM-based work in robotic applicatio…
TeLoGraF: Temporal Logic Planning via Graph-encoded Flow Matching
Yue Meng, Chuchu Fan
Learning to solve complex tasks with signal temporal logic (STL) specifications is crucial to many real-world applications. However, most previous works only consider fixed or para…
Reliable and Efficient Multi-Agent Coordination via Graph Neural Network Variational Autoencoders
Yue Meng, Nathalie Majcherczyk, Wenliang Liu +3
Multi-agent coordination is crucial for reliable multi-robot navigation in shared spaces such as automated warehouses. In regions of dense robot traffic, local coordination methods…