MIT (2020): Generalizable Autonomy for Robot Manipulation

MIT Introduction to Deep Learning : Lecture 8 Generalizable Autonomy for Robot Manipulation Lecturer: Animesh Garg (NVIDIA & University of Toronto) January 2020 For all lectures, slides, and lab materials: 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 Subscribe to stay up to date with new deep learning lectures at MIT, or follow us @MITDeepLearning on Twitter and Instagram to stay fully-connected!!