7 papers · 1 filter
Preference-Calibrated Human-in-the-Loop Reinforcement Learning for Robotic Manipulation
Zeyi Liu, Guangyao Liu, Yinuo Qu +6
Human-in-the-loop reinforcement learning (HIL-RL) improves sample efficiency in real-robot manipulation through online human intervention. However, successful trajectories may incl…
DexTeleop-0: Force-Aware Bimanual Dexterous Teleoperation with Ego-Centric Perception towards Shared Autonomy
Haichao Liu, Yuyao Jiang, Hyunsun Park +2
Fine-grained, bimanual dexterous manipulation remains a foundational challenge in robotics. Traditional teleoperation systems often fail in contact-rich tasks because embodiment ga…
iMaC: Translating Actions into Motion and Contact Images for Embodied World Models
Zhenyu Wu, Xiuwei Xu, Yukun Zhou +8
Embodied world models have emerged as a pivotal paradigm for visual robotic decision-making and interactive environment simulation. However, conventional embodied frameworks rely o…
UniManip: General-Purpose Zero-Shot Robotic Manipulation with Agentic Operational Graph
Haichao Liu, Yuanjiang Xue, Yuheng Zhou +4
Achieving general-purpose robotic manipulation requires robots to seamlessly bridge high-level semantic intent with low-level physical interaction in unstructured environments. How…
SA-VLA: Spatially-Aware Flow-Matching for Vision-Language-Action Reinforcement Learning
Xu Pan, Zhenglin Wan, Xingrui Yu +6
Vision-Language-Action (VLA) models exhibit strong generalization in robotic manipulation, yet reinforcement learning (RL) fine-tuning often degrades robustness under spatial distr…
RoboChemist: Long-Horizon and Safety-Compliant Robotic Chemical Experimentation
Zongzheng Zhang, Chenghao Yue, Haobo Xu +5
Robotic chemists promise to both liberate human experts from repetitive tasks and accelerate scientific discovery, yet remain in their infancy. Chemical experiments involve long-ho…