Title
Practical Robot Learning from Demonstrations using Deep End-to-End Training.
Abstract
Robots need to learn behaviors in intuitive and practical ways for widespread deployment in human environments. To learn a robot behavior end-to-end, we train a variant of the ResNet that maps eye-in-hand camera images to end-effector velocities. In our setup, a human teacher demonstrates the task via joystick. We show that a simple servoing task can be learned in less than an hour including data collection, model training and deployment time. Moreover, 16 minutes of demonstrations were enough for the robot to learn the task.
Year
Venue
DocType
2019
arXiv: Robotics
Journal
Volume
Citations 
PageRank 
abs/1905.09025
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
Akansel Cosgun1328.25
Thomas Rowntree200.34
Ian D. Reid35864364.59
Tom Drummond471536.33