4 papers
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…
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…
Diverse Controllable Diffusion Policy with Signal Temporal Logic
Yue Meng, Chuchu fan
Generating realistic simulations is critical for autonomous system applications such as self-driving and human-robot interactions. However, driving simulators nowadays still have d…