Learning compliant grasping and manipulation by teleoperation with adaptive force control
Chao Zeng,Shuang Li,Yiming Jiang,Qiang Li,Zhaopeng Chen,Chenguang Yang,Jianwei Zhang,Chao Zeng,Shuang Li,Yiming Jiang,Qiang Li,Zhaopeng Chen,Chenguang Yang,Jianwei Zhang
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 framework, is exploited to map human hand postures to a multi-fingered robot hand. We augment TeachNet, which is originally based on an imprecise kinematic mapping and position-only servoing, with a biomimetic learning-based c...
