3 citations · 8 across the 8 of their papers we have counts for
4 papers · 1 filter
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…
Improving Robotic Grasping Ability Through Deep Shape Generation
Junnan Jiang, Yuyang Tu, Xiaohui Xiao +4
Data-driven approaches have become a dominant paradigm for robotic grasp planning. However, the performance of these approaches is enormously influenced by the quality of the avail…
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…