3 citations · 3 across the 4 of their papers we have counts for
6 papers
Learning 6-DoF Task-oriented Grasp Detection via Implicit Estimation and Visual Affordance
Wenkai Chen, Hongzhuo Liang, Zhaopeng Chen +2
Currently, task-oriented grasp detection approaches are mostly based on pixel-level affordance detection and semantic segmentation. These pixel-level approaches heavily rely on the…
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 compliant grasping and manipulation by teleoperation with adaptive force control
Chao Zeng, Shuang Li, Yiming Jiang +4
In this work, we focus on improving the robot's dexterous capability by exploiting visual sensing and adaptive force control. TeachNet, a vision-based teleoperation learning framew…
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…