3 papers
cs.RO2026
Blind Dexterous Grasping via Real2Sim2Real Tactile Policy Learning
Shengcheng Luo, Xiyan Huang, Zhe Xu +3
Blind grasping with a dexterous hand is a crucial manipulation capability. Nevertheless, learning such tactile-only policies for real robots remains challenging due to the tactile…
cs.RO2026
ETac: A Lightweight and Efficient Tactile Simulation Framework for Learning Dexterous Manipulation
Zhe Xu, Feiyu Zhao, Xiyan Huang +1
Tactile sensors are increasingly integrated into dexterous robotic manipulators to enhance contact perception. However, learning manipulation policies that rely on tactile sensing…
cs.RO2025
TwinTac: A Wide-Range, Highly Sensitive Tactile Sensor with Real-to-Sim Digital Twin Sensor Model
Xiyan Huang, Zhe Xu, Chenxi Xiao
Robot skill acquisition processes driven by reinforcement learning often rely on simulations to efficiently generate large-scale interaction data. However, the absence of simulatio…