10 papers
Any-ttach: Quick End-effector Swapping Enables Manipulation Dexterity with Simplicity
Weizhe Ni, Jinzhou Li, Haoyu Li +3
Robotic manipulation dexterity is often pursued by building increasingly complex high-DoF multifingered hands. While many robotic hands are designed to replicate human morphology,…
CEER: Compliant End-Effector and Root Control as a Unified Interface for Hierarchical Humanoid Loco-Manipulation
Xinyuan Luo, Xingrui Chen, Xunjian Yin +6
Humanoid robots have achieved impressive locomotion performance, yet contact-rich and long-horizon manipulation remains a major bottleneck. Manipulation is inherently contact-rich…
HiPolicy: Hierarchical Multi-Frequency Action Chunking for Policy Learning
Jiyao Zhang, Zimu Han, Junhan Wang +7
Robotic imitation learning faces a fundamental trade-off between modeling long-horizon dependencies and enabling fine-grained closed-loop control. Existing fixed-frequency action c…
TwinAligner: Visual-Dynamic Alignment Empowers Physics-aware Real2Sim2Real for Robotic Manipulation
Hongwei Fan, Hang Dai, Jiyao Zhang +7
The robotics field is evolving towards data-driven, end-to-end learning, inspired by multimodal large models. However, reliance on expensive real-world data limits progress. Simula…
OPENTOUCH: Bringing Full-Hand Touch to Real-World Interaction
Yuxin Ray Song, Jinzhou Li, Rao Fu +12
The human hand is our primary interface to the physical world, yet egocentric perception rarely knows when, where, or how forcefully it makes contact. Robust wearable tactile senso…
SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training
Mingdong Wu, Lehong Wu, Yizhuo Wu +9
Autonomous learning of dexterous, long-horizon robotic skills has been a longstanding pursuit of embodied AI. Recent advances in robotic reinforcement learning (RL) have demonstrat…
ClutterDexGrasp: A Sim-to-Real System for General Dexterous Grasping in Cluttered Scenes
Zeyuan Chen, Qiyang Yan, Yuanpei Chen +6
Dexterous grasping in cluttered scenes presents significant challenges due to diverse object geometries, occlusions, and potential collisions. Existing methods primarily focus on s…
Adaptive Visuo-Tactile Fusion with Predictive Force Attention for Dexterous Manipulation
Jinzhou Li, Tianhao Wu, Jiyao Zhang +6
Effectively utilizing multi-sensory data is important for robots to generalize across diverse tasks. However, the heterogeneous nature of these modalities makes fusion challenging.…
Canonical Representation and Force-Based Pretraining of 3D Tactile for Dexterous Visuo-Tactile Policy Learning
Tianhao Wu, Jinzhou Li, Jiyao Zhang +2
Tactile sensing plays a vital role in enabling robots to perform fine-grained, contact-rich tasks. However, the high dimensionality of tactile data, due to the large coverage on de…
HGIC: A Hand Gesture Based Interactive Control System for Efficient and Scalable Multi-UAV Operations
Mengsha Hu, Jinzhou Li, Runxiang Jin +3
As technological advancements continue to expand the capabilities of multi unmanned-aerial-vehicle systems (mUAV), human operators face challenges in scalability and efficiency due…