Sessions

Wednesdays, 10-12
Fridays, 14-16
Zoom invite: this invite link

Teaching Assistants

Jung-Su Ha
Ingmar Schubert

Papers, slides & exercises

topics	material	due on
Introduction	01-introduction
Reading: The TossingBot paper https://arxiv.org/abs/1903.11239	e01-tossingBot	April 29
Lecture: Differentiable AI	02-differentiableAI
Technical Exercise	e02-endToEnd	May 6
Reading: LeTS-Drive paper https://arxiv.org/abs/1905.12197	e03-LeTS-Drive	May 20
Review Exercise	e04-LeTS-Drive-Review	May 29
Lecture: Tree Search & POMDPs	03-TreeSearchPOMDPs
Technical Exercise: Tree Search & POMDPs	e05-TreeSearchPOMDPs	June 5
Reading: PoseRBPF paper https://arxiv.org/abs/1905.09304	e06-PoseRBPF	June 17
Lecture: Probabilities \& Filtering	04-probabilities 05-filtering
Technical Exercise: Filtering	e07-filtering	June 24
Review Exercise	e08-PoseRBPF-Review	July 1
Reading: GVF paper https://sites.google.com/view/gvf-tool	e09-GVF	July 8
Lecture: Model-based RL	06-RL

Conferences

For your information, this is my top choice of conferences. But this course might focus on papers of RSS only.

• RSS (2019, 2018)
• CORL (2019, 2018)
• Also: ICRA, IROS, WAFR

Paper candidates (prelim)

• First pass through RSS 2019:
  • Improvisation through Physical Understanding: Using Novel Objects As Tools with Visual Foresight Annie Xie, Frederik Ebert, Sergey Levine, Chelsea Finn
  • TossingBot: Learning to Throw Arbitrary Objects with Residual Physics Andy Zeng, Shuran Song, Johnny Lee, Alberto Rodriquez, Thomas A.Funkouser
  • DESPOT-Alpha: Online POMDP Planning with Large State and Observation Spaces Neha Priyadarshini Garg, David Hsu, Wee Sun Lee
  • Autonomous Tool Construction Using Part Shape and Attachment Prediction Lakshmi Velayudhan Nair, Nithin Shrivatsav Srikanth, Zackory Erikson, Sonia Chernova
  • A Differentiable Augmented Lagrangian Method for Bilevel Nonlinear Optimization Benoit Landry, Zachary Manchester, Marco Pavone
  • LeTS-Drive: Driving in a Crowd by Learning from Tree Search Panpan Cai, Yuanfu Luo, Aseem Saxena, David Hsu, Wee Sun Lee
  • BayesSim: Adaptive Domain Randomization Via Probabilistic Inference for Robotics Simulators Fabio Ramos, Rafael Possas, Dieter Fox
  • Differentiable Algorithm Networks for Composable Robot Learning Peter Karkus, Xiao Ma, David Hsu, Leslie Kaelbling, Wee Sun Lee, Tomas Lozano-Perez
  • DensePhysNet: Learning Dense Physical Object Representations Via Multi-Step Dynamic Interactions Zhenjia Xu, Jiajun Wu, Andy Zeng, Joshua Tenenbaum, Shuran Song
  • PoseRBPF: A Rao-Blackwellized Particle Filter for6D Object Pose Estimation Xinke Deng, Arsalan Mousavian, Yu Xiang, Fei Xia, Timothy Bretl, Dieter Fox
  • Leveraging Experience in Lazy Search Mohak Bhardwaj, Sanjiban Choudhury, Byron Boots, Siddhartha Srinivasa
  • Toward Asymptotically-Optimal Inspection Planning Via Efficient Near-Optimal Graph Search Mengyu Fu, Alan Kuntz, Oren Salzman, Ron Alterovitz
  • Learning to Plan with Logical Automata Brandon Arak, Kiran Vodrahalli, Thomas Leech, Cristian Ioan Vasile, Mark Donahue, Daniela Rus
  • End-To-End Robotic Reinforcement Learning without Reward Engineering Avi Singh, Larry Yang, Chelsea Finn, Sergey Levine
  • Learning Robotic Manipulation through Visual Planning and Acting Angelina Wang, Thanard Kurutach, Kara Liu, Pieter Abbeel, Aviv Tamar
• Differentiable Physics and Stable Modes for Tool-Use and Manipulation Planning (RSS 2018)