24 citations · 26 across the 4 of their papers we have counts for
4 papers
Learning-based Optoelectronically Innervated Tactile Finger for Rigid-Soft Interactive Grasping
Linhan Yang, Xudong Han, Weijie Guo +3
This paper presents a novel design of a soft tactile finger with omni-directional adaptation using multi-channel optical fibers for rigid-soft interactive grasping. Machine learnin…
Design of an Optoelectronically Innervated Gripper for Rigid-Soft Interactive Grasping
Linhan Yang, Xudong Han, Weijie Guo +4
Over the past few decades, efforts have been made towards robust robotic grasping, and therefore dexterous manipulation. The soft gripper has shown their potential in robust graspi…
DeepClaw: A Robotic Hardware Benchmarking Platform for Learning Object Manipulation
Fang Wan, Haokun Wang, Xiaobo Liu +2
We present DeepClaw as a reconfigurable benchmark of robotic hardware and task hierarchy for robot learning. The DeepClaw benchmark aims at a mechatronics perspective of the robot…
Rigid-Soft Interactive Learning for Robust Grasping
Linhan Yang, Fang Wan, Haokun Wang +4
Inspired by widely used soft fingers on grasping, we propose a method of rigid-soft interactive learning, aiming at reducing the time of data collection. In this paper, we classify…