1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.RO2023
Autoencoding a Soft Touch to Learn Grasping from On-land to Underwater
Ning Guo, Xudong Han, Xiaobo Liu +6
Robots play a critical role as the physical agent of human operators in exploring the ocean. However, it remains challenging to grasp objects reliably while fully submerging under…
cs.RO2023
Jigsaw-based Benchmarking for Learning Robotic Manipulation
Xiaobo Liu, Fang Wan, Sheng Ge +3
Benchmarking provides experimental evidence of the scientific baseline to enhance the progression of fundamental research, which is also applicable to robotics. In this paper, we p…
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-…