RSS 2022 Workshop L-DOD Regular Deadline Submissions

RoboTube: Learning Household Manipulation from Human Videos with Simulated Twin Environments
haoyu Xiong, Haoyuan Fu, Jieyi Zhang, Qiang Zhang, Chen Bao, Yongxi Huang, Wenqiang Xu, Animesh Garg, Huazhe Xu, Cewu Lu
- Published: 23 Jun 2022, Last Modified: 05 May 2023
- L-DOD 2022 Poster
- Readers: Everyone
RRL: Resnet as representation for Reinforcement Learning
Rutav Shah, Vikash Kumar
- Published: 23 Jun 2022, Last Modified: 22 Oct 2023
- L-DOD 2022 Poster
- Readers: Everyone
Reinforcement Learning with Neural Radiance Fields
Danny Driess, Ingmar Schubert, Pete Florence, Yunzhu Li, Marc Toussaint
- Published: 23 Jun 2022, Last Modified: 22 Oct 2023
- L-DOD 2022 Poster
- Readers: Everyone
A Simple Approach for Visual Rearrangement: 3D Mapping and Semantic Search
Brandon Trabucco, Gunnar A Sigurdsson, Robinson Piramuthu, Gaurav S. Sukhatme, Ruslan Salakhutdinov
- Published: 23 Jun 2022, Last Modified: 05 May 2023
- L-DOD 2022 Poster
- Readers: Everyone
Dexterous Imitation Made Easy: A Learning-Based Framework for Efficient Dexterous Manipulation
Sridhar Pandian Arunachalam, Sneha Silwal, Ben Evans, Lerrel Pinto
- Published: 23 Jun 2022, Last Modified: 22 Oct 2023
- L-DOD 2022 Poster
- Readers: Everyone
The (Un)Surprising Effectiveness of Pre-Trained Vision Models for Control
Simone Parisi, Aravind Rajeswaran, Senthil Purushwalkam, Abhinav Gupta
- Published: 23 Jun 2022, Last Modified: 05 May 2023
- L-DOD 2022 Poster
- Readers: Everyone
LISA: Learning Interpretable Skill Abstractions from Language
Divyansh Garg, Skanda Vaidyanath, Kuno Kim, Jiaming Song, Stefano Ermon
- Published: 23 Jun 2022, Last Modified: 05 May 2023
- L-DOD 2022 Poster
- Readers: Everyone
Watch and Match: Supercharging Imitation with Regularized Optimal Transport
Siddhant Haldar, Denis Yarats, Lerrel Pinto
- Published: 23 Jun 2022, Last Modified: 22 Oct 2023
- L-DOD 2022 Poster
- Readers: Everyone
How Far I'll Go: Offline Goal-Conditioned Reinforcement Learning vis $f$-Advantage Regression
Yecheng Jason Ma, Jason Yan, Dinesh Jayaraman, Osbert Bastani
- Published: 23 Jun 2022, Last Modified: 05 May 2023
- L-DOD 2022 Spotlight
- Readers: Everyone
Latent-Variable Advantage-Weighted Policy Optimization for Offline Reinforcement Learning
Xi Chen, Ali Ghadirzadeh, Tianhe Yu, Yuan Gao, Jianhao Wang, Wenzhe Li, Bin Liang, Chelsea Finn, Chongjie Zhang
- Published: 23 Jun 2022, Last Modified: 05 May 2023
- L-DOD 2022 Poster
- Readers: Everyone
Challenges and Opportunities in Offline Reinforcement Learning from Visual Observations
Cong Lu, Philip J. Ball, Tim G. J. Rudner, Jack Parker-Holder, Michael A Osborne, Yee Whye Teh
- Published: 23 Jun 2022, Last Modified: 05 May 2023
- L-DOD 2022 Spotlight
- Readers: Everyone
Robotic Telekinesis: Learning a Robotic Hand Imitator by Watching Humans on YouTube
Aravind Sivakumar, Kenneth Shaw, Deepak Pathak
- Published: 23 Jun 2022, Last Modified: 22 Oct 2023
- L-DOD 2022 Poster
- Readers: Everyone
Behavior Transformers: Cloning $k$ modes with one stone
Nur Muhammad Mahi Shafiullah, Zichen Jeff Cui, Ariuntuya Altanzaya, Lerrel Pinto
- Published: 23 Jun 2022, Last Modified: 22 Oct 2023
- L-DOD 2022 Poster
- Readers: Everyone
Can Foundation Models Perform Zero-Shot Task Specification For Robot Manipulation?
Yuchen Cui, Scott Niekum, Abhinav Gupta, Vikash Kumar, Aravind Rajeswaran
- Published: 23 Jun 2022, Last Modified: 05 May 2023
- L-DOD 2022 Spotlight
- Readers: Everyone
A Dataset and Benchmark for Learning the Kinematics of Concentric Tube Continuum Robots
Reinhard M Grassmann, Ryan Zeyuan Chen, Nan Liang, Jessica Burgner-Kahrs
- Published: 23 Jun 2022, Last Modified: 05 May 2023
- L-DOD 2022 Poster
- Readers: Everyone
Learning from Imperfect Demonstrations via Adversarial Confidence Transfer
Zhangjie Cao, Zihan Wang, Dorsa Sadigh
- Published: 23 Jun 2022, Last Modified: 05 May 2023
- L-DOD 2022 Poster
- Readers: Everyone
Offline RL at Multiple Frequencies
Kaylee Burns, Tianhe Yu, Chelsea Finn, Karol Hausman
- Published: 23 Jun 2022, Last Modified: 05 May 2023
- L-DOD 2022 Poster
- Readers: Everyone