1 citations · 1 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.RO2023★ 1 cited
TacGNN:Learning Tactile-based In-hand Manipulation with a Blind Robot
Linhan Yang, Bidan Huang, Qingbiao Li +4
In this paper, we propose a novel framework for tactile-based dexterous manipulation learning with a blind anthropomorphic robotic hand, i.e. without visual sensing. First, object-…