6 citations · 8 across the 4 of their papers we have counts for
6 papers · 1 filter
Towards Precise Model-free Robotic Grasping with Sim-to-Real Transfer Learning
Lei Zhang, Kaixin Bai, Zhaopeng Chen +2
Precise robotic grasping of several novel objects is a huge challenge in manufacturing, automation, and logistics. Most of the current methods for model-free grasping are disadvant…
Sim-to-Real Transfer of Robotic Assembly with Visual Inputs Using CycleGAN and Force Control
Chengjie Yuan, Yunlei Shi, Qian Feng +4
Recently, deep reinforcement learning (RL) has shown some impressive successes in robotic manipulation applications. However, training robots in the real world is nontrivial owing…
Maximizing the Use of Environmental Constraints: A Pushing-Based Hybrid Position/Force Assembly Skill for Contact-Rich Tasks
Yunlei Shi, Zhaopeng Chen, Lin Cong +6
The need for contact-rich tasks is rapidly growing in modern manufacturing settings. However, few traditional robotic assembly skills consider environmental constraints during task…
Impedance Adaptation by Reinforcement Learning with Contact Dynamic Movement Primitives
Chunyang Chang, Kevin Haninger, Yunlei Shi +3
Dynamic movement primitives (DMPs) allow complex position trajectories to be efficiently demonstrated to a robot. In contact-rich tasks, where position trajectories alone may not b…
Combining Learning from Demonstration with Learning by Exploration to Facilitate Contact-Rich Tasks
Yunlei Shi, Zhaopeng Chen, Yansong Wu +5
Collaborative robots are expected to be able to work alongside humans and in some cases directly replace existing human workers, thus effectively responding to rapid assembly line…
Proactive Action Visual Residual Reinforcement Learning for Contact-Rich Tasks Using a Torque-Controlled Robot
Yunlei Shi, Zhaopeng Chen, Hongxu Liu +5
Contact-rich manipulation tasks are commonly found in modern manufacturing settings. However, manually designing a robot controller is considered hard for traditional control metho…