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Qianrun Chen

2 accepted papers

2025

GAP-RL: Grasps as Points for RL Towards Dynamic Object Grasping

RA-L 2025

Dynamic grasping of moving objects in complex, continuous motion scenarios remains challenging. Reinforcement Learning (RL) has been applied in various robotic manipulation tasks, benefiting from its closed-loop property. However, existing RL-based methods do not fully explore the potential for enha

Cited by 7SourceScholar
2025

RobustLight: Improving Robustness via Diffusion Reinforcement Learning for Traffic Signal Control

ICML 2025poster

Reinforcement Learning (RL) optimizes Traffic Signal Control (TSC) to reduce congestion and emissions, but real-world TSC systems face challenges like adversarial attacks and missing data, leading to incorrect signal decisions and increased congestion. Existing methods, limited to offline data predi…

Cited by 0SourcePDFScholar