9 papers
FWBC-VLA: Force-Aware Whole-Body Compensation for Contact-Rich Loco-Manipulation
Yutian Zhang, Siyuan Ma, Liwen Yang +6
Contact-rich loco-manipulation requires a bridge between semantic action generation and physical interaction control. Existing Vision-language-action (VLA) models generate task-lev…
KAI: A Kinematic-Aware Interface for Data-Efficient Articulated Object Manipulation
Yaping Li, Zhaxizhuoma, Qiaojun Yu +3
Articulated object manipulation requires an understanding of kinematic structure that is difficult and costly to learn from robot demonstrations alone. We introduce the Kinematic-A…
SIM1: Physics-Aligned Simulator as Zero-Shot Data Scaler in Deformable Worlds
Yunsong Zhou, Hangxu Liu, Xuekun Jiang +12
Robotic manipulation with deformable objects represents a data-intensive regime in embodied learning, where shape, contact, and topology co-evolve in ways that far exceed the varia…
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…
Towards Human-Like Manipulation through RL-Augmented Teleoperation and Mixture-of-Dexterous-Experts VLA
Tutian Tang, Xingyu Ji, Wanli Xing +7
While Vision-Language-Action (VLA) models have demonstrated remarkable success in robotic manipulation, their application has largely been confined to low-degree-of-freedom end-eff…
SkillVLA: Tackling Combinatorial Diversity in Dual-Arm Manipulation via Skill Reuse
Xuanran Zhai, Zekai Huang, Longyan Wu +5
Recent progress in vision-language-action (VLA) models has demonstrated strong potential for dual-arm manipulation, enabling complex behaviors and generalization to unseen environm…
InternVLA-A1: Unifying Understanding, Generation and Action for Robotic Manipulation
Junhao Cai, Zetao Cai, Jiafei Cao +39
Prevalent Vision-Language-Action (VLA) models are typically built upon Multimodal Large Language Models (MLLMs) and demonstrate exceptional proficiency in semantic understanding, b…
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 perform complex, contact-rich manipulation. Imitation learning provides a route to such skills, but collecting human demonstrations with accurate hand actio…
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…