MIT Introduction to Deep Learning 6.S191: Lecture 8
Generalizable Autonomy for Robot Manipulation
Lecturer: Animesh Garg (NVIDIA & University of Toronto)
January 2020
For all lectures, slides, and lab materials: http://introtodeeplearning.com
Lecture Outline
0:00 – Introduction
3:45 – Achieving generalizable autonomy
4:19 – Leveraging imitation learning
6:08 – Learning visuo-motor policies
13:09 – Learning skills
16:38 – Off-policy RL + AC-Teach
22:02 – Compositional planning
27:20 – Model-based RL
34:37 – Leveraging task structure
36:35 – Neural task programming (NTP)
43:04 – Data for robotics
44:24 – RoboTurk
45:54 – Summary
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