7 papers
RoboRouter: Training-Free Policy Routing for Robotic Manipulation
Yiteng Chen, Zhe Cao, Hongjia Ren +9
Research on robotic manipulation has developed a diverse set of policy paradigms, including vision-language-action (VLA) models, vision-action (VA) policies, and code-based composi…
Enforcing Human-like Kinematics in Dexterous Piano Playing via Adversarial Posture Regularization
Bin Qiu, Yanming Shao, Guanyu Cai +1
Reinforcement learning can train bimanual dexterous hands to play piano in physics simulation with high note accuracy, but for high-DoF dexterous hands, relying solely on task rewa…
V2P-Manip: Learning Dexterous Manipulation from Monocular Human Videos
Kaihan Chen, Yanming Shao, Haifeng Ji +2
Achieving autonomous robotic dexterous manipulation requires precise, human-like action sequences at scale. As a scalable supplement to costly teleoperation data, extracting trajec…
SynManDex: Synthesizing Human-like Dexterous Grasps from Synthetic Human Pre-Grasps
Yanming Shao, Zanxin Chen, Wenwei Lin +5
Human hand-object interactions encode functional intent, but direct transfer to robotic hands often fails under morphology, contact, and reachability constraints. We present SynMan…
BORA: Bridging Offline Reinforcement Learning and Online Residual Adaptation for Real-World Dexterous VLA Models
Zhongxi Chen, Yifan Han, Yanming Shao +5
Vision-Language-Action (VLA) models have emerged as a promising paradigm for grounding visual-language understanding into real-world robotic manipulation. However, dexterous manipu…
DexHiL: A Human-in-the-Loop Framework for Vision-Language-Action Model Post-Training in Dexterous Manipulation
Yifan Han, Zhongxi Chen, Yuxuan Zhao +5
While Vision-Language-Action (VLA) models have demonstrated promising generalization capabilities in robotic manipulation, deploying them on specific and complex downstream tasks s…