24 citations · 40 across the 4 of their papers we have counts for
4 papers
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…
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…
Reconfigurable Design for Omni-adaptive Grasp Learning
Fang Wan, Haokun Wang, Jiyuan Wu +3
The engineering design of robotic grippers presents an ample design space for optimization towards robust grasping. In this paper, we adopt the reconfigurable design of the robotic…