OHPL: One-shot Hand-eye Policy Learner
Changjae Oh,Yik Lung Pang,Andrea Cavallaro,Changjae Oh,Yik Lung Pang,Andrea Cavallaro
The control of a robot for manipulation tasks generally relies on object detection and pose estimation. An attractive alternative is to learn control policies directly from raw input data. However, this approach is time-consuming and expensive since learning the policy requires many trials with robot actions in the physical environment. To reduce the training cost, the policy can be learned in sim...
