2 citations · 3 across the 8 of their papers we have counts for
10 papers
Spark-0: Scaling Spatially Aligned Tactile Pretraining for Robot Dexterous Manipulation
Tianxing Chen, Wenwei Lin, Chuqiao Lyu +19
Generalist robot policies benefit from large-scale visual pretraining but often struggle with contact-rich dexterous manipulation, where force, compliance, and incipient slip are h…
Towards a Systematic Study of Embodied System 2 over Full Task Execution Cycles
Yuxi Wei, Ye Fang, Shuai Yang +3
An embodied brain, or System 2, must turn an abstract goal into actions while discovering relevant scene conditions and checking whether executed skills achieved their intended eff…
SpaceDex: Generalizable Dexterous Grasping in Tiered Workspaces
Wensheng Wang, Chuanjun Guo, Wei Wei +2
Generalizable grasping with high-degree-of-freedom (DoF) dexterous hands remains challenging in tiered workspaces, where occlusion, narrow clearances, and height-dependent constrai…
CEI: A Unified Interface for Cross-Embodiment Visuomotor Policy Learning in 3D Space
Tong Wu, Shoujie Li, Junhao Gong +4
Robotic foundation models trained on large-scale manipulation datasets have shown promise in learning generalist policies, but they often overfit to specific viewpoints, robot arms…
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…
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…
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…
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…
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…
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…