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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