Publications (28)
SAGCI-System: Towards Sample-Efficient, Generalizable, Compositional, and Incremental Robot Learning
Jun Lv, Qiaojun Yu, Lin Shao +3
Building general-purpose robots to perform a diverse range of tasks in a large variety of environments in the physical world at the human level is extremely challenging. It require…
MILE: A Mechanically Isomorphic Hand Exoskeleton and Visuotactile Robotic Hand for Data Collection in Dexterous Manipulation
Jinda Du, Jieji Ren, Qiaojun Yu +6
Dexterous robotic hands are expected to perform complex, contact-rich object manipulation, but learning such skills remains challenging because high-dimensional hands require high-…
ForceFlow: Learning to Feel and Act via Contact-Driven Flow Matching
Shuoheng Zhang, Yifu Yuan, Hongyao Tang +7
Existing imitation learning methods enable robots to interact autonomously with the physical environment. However, contact-rich manipulation tasks remain a significant challenge du…
ForceVLA: Enhancing VLA Models with a Force-aware MoE for Contact-rich Manipulation
Jiawen Yu, Hairuo Liu, Qiaojun Yu +9
Vision-Language-Action (VLA) models have advanced general-purpose robotic manipulation by leveraging pretrained visual and linguistic representations. However, they struggle with c…
VFP: Variational Flow-Matching Policy for Multi-Modal Robot Manipulation
Xuanran Zhai, Qianyou Zhao, Qiaojun Yu +1
Flow-matching-based policies have recently emerged as a promising approach for learning-based robot manipulation, offering significant acceleration in action sampling compared to d…
ForceVLA2: Unleashing Hybrid Force-Position Control with Force Awareness for Contact-Rich Manipulation
Yang Li, Zhaxizhuoma, Hongru Jiang +11
Embodied intelligence for contact-rich manipulation has predominantly relied on position control, while explicit awareness and regulation of interaction forces remain under-explore…