57 citations · 63 across the 19 of their papers we have counts for
23 papers
TacOT: Learning Contact-Rich Dexterous Manipulation from Human Demonstrations via Tactile-Guided Optimal Transport
Xingting Li, Yifan Han, Zijian Lin +4
Learning contact-rich dexterous manipulation from human demonstrations provides a scalable source of interaction data, yet transferring such skills to robots remains challenging du…
BiView-Touch: Learning Bimanual Tactile Representations by Cross-Hand Completion
Chenxin Liang, Youchen Lai, Chuqiao Lyu +3
Bimanual interaction produces complementary tactile views of the same physical process, yet existing tactile representation learning largely models the two hands independently or c…
DexTouch-WM: Learning Action-Conditioned Tactile World Models from Human Touch for Dexterous Robot Manipulation
Yan Qin, Yue Chen, Wenwei Lin +9
Learning predictive models of contact-rich dexterous manipulation requires dense tactile interaction, but such data are costly to scale on real robots and remain tied to embodiment…
TouchSight: Bare-Handed Tactile Prediction from Egocentric Video via Generative Visual Augmentation
Danyan Zhou, Jinxuan Lu, Jiawei Lin +3
Tactile signals provide direct contact and force measurements that are essential for understanding physical interactions and enabling dexterous robotic manipulation. However, tacti…
TouchAnything: A Dataset and Framework for Bimanual Tactile Estimation from Egocentric Video
Jianyi Zhou, Ziteng Gao, Feiyang Hong +11
Egocentric human video data, which captures rich human-environment interactions and can be collected at scale, has become a key driver of embodied intelligence research. However, e…
Master Micro Residual Correction with Adaptive Tactile Fusion and Force-Mixed Control for Contact-Rich Manipulation
Xingting Li, Yifan Xie, Han Liu +4
Robotic contact-rich and fine-grained manipulation remains a significant challenge due to complex interaction dynamics and the competing requirements of multi-timescale control. Wh…
PACT-WAM: Predicting Actions and Visual Foresight with Compact Temporal Encoding for Robot Manipulation
Jingjing Fan, Yushan Liu, Shoujie Li +6
Robot manipulation uses temporal context to select actions and visual foresight to assess their consequences, yet dense representations of past and future observations incur substa…
UMIGen: A Unified Framework for Egocentric Point Cloud Generation and Cross-Embodiment Robotic Imitation Learning
Yan Huang, Shoujie Li, Xingting Li +1
Data-driven robotic learning faces an obvious dilemma: robust policies demand large-scale, high-quality demonstration data, yet collecting such data remains a major challenge owing…
FlexiCup: Wireless Multimodal Suction Cup with Dual-Zone Vision-Tactile Sensing
Junhao Gong, Shoujie Li, Kit-Wa Sou +8
Conventional suction cups lack sensing capabilities for contact-aware manipulation in unstructured environments. This paper presents FlexiCup, a multimodal suction cup with wireles…
Universal Visuo-Tactile Video Understanding for Embodied Interaction
Yifan Xie, Mingyang Li, Shoujie Li +5
Tactile perception is essential for embodied agents to understand physical attributes of objects that cannot be determined through visual inspection alone. While existing approache…
VTire: A Bimodal Visuotactile Tire with High-Resolution Sensing Capability
Shoujie Li, Jianle Xu, Tong Wu +5
Developing smart tires with high sensing capability is significant for improving the moving stability and environmental adaptability of wheeled robots and vehicles. However, due to…
PUGS: Zero-shot Physical Understanding with Gaussian Splatting
Yinghao Shuai, Ran Yu, Yuantao Chen +9
Current robotic systems can understand the categories and poses of objects well. But understanding physical properties like mass, friction, and hardness, in the wild, remains chall…
Exo-ViHa: A Cross-Platform Exoskeleton System with Visual and Haptic Feedback for Efficient Dexterous Skill Learning
Xintao Chao, Shilong Mu, Yushan Liu +4
Imitation learning has emerged as a powerful paradigm for robot skills learning. However, traditional data collection systems for dexterous manipulation face challenges, including…
AVR: Active Vision-Driven Precise Robot Manipulation with Viewpoint and Focal Length Optimization
Yushan Liu, Shilong Mu, Xintao Chao +7
Robotic manipulation in complex scenes demands precise perception of task-relevant details, yet fixed or suboptimal viewpoints often impair fine-grained perception and induce occlu…
MuxHand: A Cable-driven Dexterous Robotic Hand Using Time-division Multiplexing Motors
Jianle Xu, Shoujie Li, Hong Luo +4
The robotic dexterous hand is responsible for both grasping and dexterous manipulation. The number of motors directly influences both the dexterity and the cost of such systems. In…
MoDex: Planning High-Dimensional Dexterous Control via Learning Neural Internal Models
Tong Wu, Shoujie Li, Chuqiao Lyu +3
Controlling hands in high-dimensional action space has been a longstanding challenge, yet humans naturally perform dexterous tasks with ease. In this paper, we draw inspiration fro…
When Vision Meets Touch: A Contemporary Review for Visuotactile Sensors from the Signal Processing Perspective
Shoujie Li, Zihan Wang, Changsheng Wu +6
Tactile sensors, which provide information about the physical properties of objects, are an essential component of robotic systems. The visuotactile sensing technology with the mer…
Chemistry3D: Robotic Interaction Benchmark for Chemistry Experiments
Shoujie Li, Yan Huang, Changqing Guo +4
The advent of simulation engines has revolutionized learning and operational efficiency for robots, offering cost-effective and swift pipelines. However, the lack of a universal si…
Point-Wise Vibration Pattern Production via a Sparse Actuator Array for Surface Tactile Feedback
Xiaosa Li, Runze Zhao, Chengyue Lu +2
Surface vibration tactile feedback is capable of conveying various semantic information to humans via the handheld electronic devices, like smartphone, touch panel,and game control…
DeformNet: Latent Space Modeling and Dynamics Prediction for Deformable Object Manipulation
Chenchang Li, Zihao Ai, Tong Wu +3
Manipulating deformable objects is a ubiquitous task in household environments, demanding adequate representation and accurate dynamics prediction due to the objects' infinite degr…
Dual-modal Tactile E-skin: Enabling Bidirectional Human-Robot Interaction via Integrated Tactile Perception and Feedback
Shilong Mu, Runze Zhao, Zenan Lin +5
To foster an immersive and natural human-robot interaction, the implementation of tactile perception and feedback becomes imperative, effectively bridging the conventional sensory…
SATac: A Thermoluminescence Enabled Tactile Sensor for Concurrent Perception of Temperature, Pressure, and Shear
Ziwu Song, Ran Yu, Xuan Zhang +5
Most vision-based tactile sensors use elastomer deformation to infer tactile information, which can not sense some modalities, like temperature. As an important part of human tacti…
Growing from Exploration: A self-exploring framework for robots based on foundation models
Shoujie Li, Ran Yu, Tong Wu +3
Intelligent robot is the ultimate goal in the robotics field. Existing works leverage learning-based or optimization-based methods to accomplish human-defined tasks. However, the c…