2 citations · 4 across the 5 of their papers we have counts for
5 papers
Robotic Assembly Control Reconfiguration Based on Transfer Reinforcement Learning for Objects with Different Geometric Features
Yuhang Gai, Bing Wang, Jiwen Zhang +2
Robotic force-based compliance control is a preferred approach to achieve high-precision assembly tasks. When the geometric features of assembly objects are asymmetric or irregular…
Local Connection Reinforcement Learning Method for Efficient Control of Robotic Peg-in-Hole Assembly
Yuhang Gai, Jiwen Zhang, Dan Wu +1
Traditional control methods of robotic peg-in-hole assembly rely on complex contact state analysis. Reinforcement learning (RL) is gradually becoming a preferred method of controll…
Progressive extension of reinforcement learning action dimension for asymmetric assembly tasks
Yuhang Gai, Jiuming Guo, Dan Wu +1
Reinforcement learning (RL) is always the preferred embodiment to construct the control strategy of complex tasks, like asymmetric assembly tasks. However, the convergence speed of…
Feature-Based Compliance Control for Peg-in-Hole Assembly with Clearance or Interference Fit
Yuhang Gai, Jiuming Guo, Dan Wu +1
This paper aims at solving mass precise peg-in-hole assembly. First, a feature space and a response space are constructed according to the relative pose and equivalent forces and m…
Fast Skill Learning for Variable Compliance Robotic Assembly
Tianyu Ren, Yunfei Dong, Dan Wu +1
The robotic assembly represents a group of benchmark problems for reinforcement learning and variable compliance control that features sophisticated contact manipulation. One of th…