# Projects using robomimic

A list of projects and papers that use **robomimic**. If you would like to add your work to this list, please send the paper or project information to Ajay Mandlekar (<amandlek@cs.stanford.edu>).

## 2023

- [Imitating Task and Motion Planning with Visuomotor Transformers](https://arxiv.org/abs/2305.16309). Murtaza Dalal, Ajay Mandlekar\*, Caelan Garrett\*, Ankur Handa, Ruslan Salakhutdinov, Dieter Fox
- [Data Quality in Imitation Learning](https://arxiv.org/abs/2306.02437). Suneel Belkhale, Yuchen Cui, Dorsa Sadigh
- [Coherent Soft Imitation Learning](https://arxiv.org/abs/2305.16498). Joe Watson, Sandy H. Huang, Nicolas Heess
- [Inverse Preference Learning: Preference-based RL without a Reward Function](https://arxiv.org/abs/2305.15363). Joey Hejna, Dorsa Sadigh
- [Sequence Modeling is a Robust Contender for Offline Reinforcement Learning](https://arxiv.org/abs/2305.14550). Prajjwal Bhargava, Rohan Chitnis, Alborz Geramifard, Shagun Sodhani, Amy Zhang
- [Diffusion Co-Policy for Synergistic Human-Robot Collaborative Tasks](https://arxiv.org/abs/2305.12171). Eley Ng, Ziang Liu, Monroe Kennedy III
- [Zero-shot Preference Learning for Offline RL via Optimal Transport](https://arxiv.org/abs/2306.03615). Runze Liu, Yali Du, Fengshuo Bai, Jiafei Lyu, Xiu Li
- [Seeing the Pose in the Pixels: Learning Pose-Aware Representations in Vision Transformers](https://arxiv.org/abs/2306.09331). Dominick Reilly, Aman Chadha, Srijan Das
- [Get Back Here: Robust Imitation by Return-to-Distribution Planning](https://arxiv.org/abs/2305.01400). Geoffrey Cideron, Baruch Tabanpour, Sebastian Curi, Sertan Girgin, Leonard Hussenot, Gabriel Dulac-Arnold, Matthieu Geist, Olivier Pietquin, Robert Dadashi
- [Preference Transformer: Modeling Human Preferences using Transformers for RL](https://arxiv.org/abs/2303.00957). Changyeon Kim, Jongjin Park, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee
- [MimicPlay: Long-Horizon Imitation Learning by Watching Human Play](https://arxiv.org/abs/2302.12422). Chen Wang, Linxi Fan, Jiankai Sun, Ruohan Zhang, Li Fei-Fei, Danfei Xu, Yuke Zhu, Anima Anandkumar
- [Diffusion Policy: Visuomotor Policy Learning via Action Diffusion](https://arxiv.org/abs/2303.04137). Cheng Chi, Siyuan Feng, Yilun Du, Zhenjia Xu, Eric Cousineau, Benjamin Burchfiel, Shuran Song
- [ORBIT: A Unified Simulation Framework for Interactive Robot Learning Environments](https://arxiv.org/abs/2301.04195). Mayank Mittal, Calvin Yu, Qinxi Yu, Jingzhou Liu, Nikita Rudin, David Hoeller, Jia Lin Yuan, Pooria Poorsarvi Tehrani, Ritvik Singh, Yunrong Guo, Hammad Mazhar, Ajay Mandlekar, Buck Babich, Gavriel State, Marco Hutter, Animesh Garg
- [PLEX: Making the Most of the Available Data for Robotic Manipulation Pretraining](https://arxiv.org/abs/2303.08789). Garrett Thomas, Ching-An Cheng, Ricky Loynd, Vibhav Vineet, Mihai Jalobeanu, Andrey Kolobov
- [Behavior Retrieval: Few-Shot Imitation Learning by Querying Unlabeled Datasets](https://arxiv.org/abs/2304.08742). Maximilian Du, Suraj Nair, Dorsa Sadigh, Chelsea Finn
- [Mind the Gap: Offline Policy Optimization for Imperfect Rewards](https://arxiv.org/abs/2302.01667). Jianxiong Li, Xiao Hu, Haoran Xu, Jingjing Liu, Xianyuan Zhan, Qing-Shan Jia, Ya-Qin Zhang

## 2022

- [Learning and Retrieval from Prior Data for Skill-based Imitation Learning](https://arxiv.org/abs/2210.11435). Soroush Nasiriany, Tian Gao, Ajay Mandlekar, Yuke Zhu
- [VIOLA: Imitation Learning for Vision-Based Manipulation with Object Proposal Priors](https://arxiv.org/abs/2210.11339). Yifeng Zhu, Abhishek Joshi, Peter Stone, Yuke Zhu
- [Robot Learning on the Job: Human-in-the-Loop Autonomy and Learning During Deployment](https://arxiv.org/abs/2211.08416). Huihan Liu, Soroush Nasiriany, Lance Zhang, Zhiyao Bao, Yuke Zhu
- [Data-Efficient Pipeline for Offline Reinforcement Learning with Limited Data](https://arxiv.org/abs/2210.08642). Allen Nie, Yannis Flet-Berliac, Deon R. Jordan, William Steenbergen, Emma Brunskill
- [Eliciting Compatible Demonstrations for Multi-Human Imitation Learning](https://arxiv.org/abs/2210.08073). Kanishk Gandhi, Siddharth Karamcheti, Madeline Liao, Dorsa Sadigh
- [Masked Imitation Learning: Discovering Environment-Invariant Modalities in Multimodal Demonstrations](https://arxiv.org/abs/2209.07682). Yilun Hao, Ruinan Wang, Zhangjie Cao, Zihan Wang, Yuchen Cui, Dorsa Sadigh
- [Know Your Boundaries: The Necessity of Explicit Behavioral Cloning in Offline RL](https://arxiv.org/abs/2206.00695). Wonjoon Goo, Scott Niekum
- [HEETR: Pretraining for Robotic Manipulation on Heteromodal Data](https://openreview.net/forum?id=1_XARk3k-M). Garrett Thomas, Andrey Kolobov, Ching-An Cheng, Vibhav Vineet, Mihai Jalobeanu
- [Translating Robot Skills: Learning Unsupervised Skill Correspondences Across Robots](https://proceedings.mlr.press/v162/shankar22a.html). Tanmay Shankar, Yixin Lin, Aravind Rajeswaran, Vikash Kumar, Stuart Anderson, Jean Oh
- [Active Predicting Coding: Brain-Inspired Reinforcement Learning for Sparse Reward Robotic Control Problems](https://arxiv.org/abs/2209.09174). Alexander Ororbia, Ankur Mali
- [Imitation Learning by Estimating Expertise of Demonstrators](https://arxiv.org/abs/2202.01288). Mark Beliaev, Andy Shih, Stefano Ermon, Dorsa Sadigh, Ramtin Pedarsani

## 2021

- [RLDS: an Ecosystem to Generate, Share and Use Datasets in Reinforcement Learning](https://arxiv.org/abs/2111.02767). Sabela Ramos, Sertan Girgin, Léonard Hussenot, Damien Vincent, Hanna Yakubovich, Daniel Toyama, Anita Gergely, Piotr Stanczyk, Raphael Marinier, Jeremiah Harmsen, Olivier Pietquin, Nikola Momchev
- [Error-Aware Imitation Learning from Teleoperation Data for Mobile Manipulation](https://arxiv.org/abs/2112.05251). Josiah Wong, Albert Tung, Andrey Kurenkov, Ajay Mandlekar, Li Fei-Fei, Silvio Savarese, Roberto Martín-Martín
- [Generalization Through Hand-Eye Coordination: An Action Space for Learning Spatially-Invariant Visuomotor Control](https://arxiv.org/abs/2103.00375). Chen Wang, Rui Wang, Danfei Xu, Ajay Mandlekar, Li Fei-Fei, Silvio Savarese
- [Deep Affordance Foresight: Planning Through What Can Be Done in the Future](https://arxiv.org/abs/2011.08424). Danfei Xu, Ajay Mandlekar, Roberto Martín-Martín, Yuke Zhu, Silvio Savarese, Li Fei-Fei
- [Learning Multi-Arm Manipulation Through Collaborative Teleoperation](https://arxiv.org/abs/2012.06738). Albert Tung, Josiah Wong, Ajay Mandlekar, Roberto Martín-Martín, Yuke Zhu, Li Fei-Fei, Silvio Savarese
- [Learning to Generalize Across Long-Horizon Tasks from Human Demonstrations](https://arxiv.org/abs/2003.06085). Ajay Mandlekar\*, Danfei Xu\*, Roberto Martín-Martín, Silvio Savarese, Li Fei-Fei

## 2020

- [Human-in-the-Loop Imitation Learning using Remote Teleoperation](https://arxiv.org/abs/2012.06733). Ajay Mandlekar, Danfei Xu, Roberto Martín-Martín, Yuke Zhu, Li Fei-Fei, Silvio Savarese
- [IRIS: Implicit Reinforcement without Interaction at Scale for Learning Control from Offline Robot Manipulation Data](https://arxiv.org/abs/1911.05321). Ajay Mandlekar, Fabio Ramos, Byron Boots, Silvio Savarese, Li Fei-Fei, Animesh Garg, Dieter Fox