3 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.RO2023
Crossing the Reality Gap in Tactile-Based Learning
Ya-Yen Tsai, Bidan Huang, Yu Zheng +3
Tactile sensors are believed to be essential in robotic manipulation, and prior works often rely on experts to reason the sensor feedback and design a controller. With the recent a…
cs.RO2023
Dexterous In-Hand Manipulation of Slender Cylindrical Objects through Deep Reinforcement Learning with Tactile Sensing
Wenbin Hu, Bidan Huang, Wang Wei Lee +3
Continuous in-hand manipulation is an important physical interaction skill, where tactile sensing provides indispensable contact information to enable dexterous manipulation of sma…
cs.RO2021★ 3 cited
Explainable Hierarchical Imitation Learning for Robotic Drink Pouring
Dandan Zhang, Yu Zheng, Qiang Li +3
To accurately pour drinks into various containers is an essential skill for service robots. However, drink pouring is a dynamic process and difficult to model. Traditional deep imi…