3 citations · 3 across the 3 of their papers we have counts for
5 papers
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…
Learning Friction Model for Magnet-actuated Tethered Capsule Robot
Yi Wang, Yuyang Tu, Yuchen He +4
The potential diagnostic applications of magnet-actuated capsules have been greatly increased in recent years. For most of these potential applications, accurate position control o…
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…
Center-of-Mass-based Robust Grasp Planning for Unknown Objects Using Tactile-Visual Sensors
Qian Feng, Zhaopeng Chen, Jun Deng +3
An unstable grasp pose can lead to slip, thus an unstable grasp pose can be predicted by slip detection. A regrasp is required afterwards to correct the grasp pose in order to fini…