Ajay U. Mandlekar – Publications

For a complete list please see Google Scholar.

PhD Thesis

Building Robot Intelligence by Scaling Human Supervision

[pdf] [video]

Preprints

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Voyager: An Open-Ended Embodied Agent with Large Language Models

Guanzhi Wang, Yuqi Xie, Yunfan Jiang*, Ajay Mandlekar*, Chaowei Xiao, Yuke Zhu, Linxi Fan†, Anima Anandkumar†

2023

[pdf] [website] [code]

Publications

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MimicGen: A Data Generation System for Scalable Robot Learning using Human Demonstrations

Ajay Mandlekar, Soroush Nasiriany*, Bowen Wen*, Iretiayo Akinola, Yashraj Narang, Linxi Fan, Yuke Zhu, Dieter Fox

CoRL 2023

Oral at CoRL 2023 Towards Generalist Robots Workshop

[pdf] [website] [code]

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Human-in-the-Loop Task and Motion Planning for Imitation Learning

Ajay Mandlekar*, Caelan Garrett*, Danfei Xu, Dieter Fox

CoRL 2023

Oral at CoRL 2023 Deployable Workshop

[pdf] [website]

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Imitating Task and Motion Planning with Visuomotor Transformers

Murtaza Dalal, Ajay Mandlekar*, Caelan Garrett*, Ankur Handa, Ruslan Salakhutdinov, Dieter Fox

CoRL 2023

[pdf] [website] [code]

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Active Task Randomization: Learning Visuomotor Skills for Sequential Manipulation by Proposing Feasible and Novel Tasks

Kuan Fang*, Toki Migimatsu*, Ajay Mandlekar, Li Fei-Fei, Jeannette Bohg

IROS 2023

[pdf] [website]

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ORBIT: A Unified Simulation Framework for Interactive Robot Learning Environments

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

IEEE Robotics and Automation Letters (RA-L) and ICRA 2023

[pdf] [website] [code]

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Learning and Retrieval from Prior Data for Skill-based Imitation Learning

Soroush Nasiriany, Tian Gao, Ajay Mandlekar, Yuke Zhu

CoRL 2022

[pdf] [website]

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MoCoDA: Model-based Counterfactual Data Augmentation

Silviu Pitis, Elliot Creager, Ajay Mandlekar, Animesh Garg

NeurIPS 2022

[pdf] [website] [code]

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MineDojo: Building Open-Ended Embodied Agents with Internet-Scale Knowledge

Linxi Fan, Guanzhi Wang*, Yunfan Jiang*, Ajay Mandlekar, Yuncong Yang, Haoyi Zhu, Andrew Tang, De-An Huang, Yuke Zhu, Anima Anandkumar

NeurIPS 2022 Datasets and Benchmarks Track

Outstanding Paper Award

[pdf] [website] [code] [blog]

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What Matters in Learning from Offline Human Demonstrations for Robot Manipulation

Ajay Mandlekar, Danfei Xu, Josiah Wong, Soroush Nasiriany, Chen Wang, Rohun Kulkarni, Li Fei-Fei, Silvio Savarese, Yuke Zhu, Roberto Martín-Martín

CoRL 2021

Oral (6.5% acceptance)

[pdf] [website] [video] [code] [blog] [talk]

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Error-Aware Imitation Learning from Teleoperation Data for Mobile Manipulation

Josiah Wong, Albert Tung, Andrey Kurenkov, Ajay Mandlekar, Li Fei-Fei, Silvio Savarese, Roberto Martín-Martín

CoRL 2021

[pdf] [website] [video]

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S4RL: Surprisingly Simple Self-Supervision for Offline Reinforcement Learning

Samarth Sinha, Ajay Mandlekar, Animesh Garg

CoRL 2021

[pdf]

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Generalization through Hand-Eye Coordination: An Action Space for Learning Spatially-Invariant Visuomotor Control

Chen Wang*, Rui Wang*, Ajay Mandlekar, Li Fei-Fei, Silvio Savarese, Danfei Xu

IROS 2021

[pdf] [website]

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Learning Multi-Arm Manipulation Through Collaborative Teleoperation

Albert Tung*, Josiah Wong*, Ajay Mandlekar, Roberto Martín-Martín, Yuke Zhu, Li Fei-Fei, Silvio Savarese

ICRA 2021

Best Multi-Robotic Systems Paper Finalist

[pdf] [website] [video]

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Deep Affordance Foresight: Planning Through What Can Be Done in the Future

Danfei Xu, Ajay Mandlekar, Roberto Martín-Martín, Yuke Zhu, Silvio Savarese, Li Fei-Fei

ICRA 2021

[pdf] [website] [video] [talk]

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Human-in-the-Loop Imitation Learning using Remote Teleoperation

Ajay Mandlekar, Danfei Xu*, Roberto Martin-Martin*, Yuke Zhu, Li Fei-Fei, Silvio Savarese

Technical Report 2020

[pdf] [website] [video]

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Learning to Generalize Across Long-Horizon Tasks from Human Demonstrations

Ajay Mandlekar*, Danfei Xu*, Roberto Martín-Martín, Silvio Savarese, Li Fei-Fei

RSS 2020

[pdf] [website] [video]

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IRIS: Implicit Reinforcement without Interaction at Scale for Learning Control from Offline Robot Manipulation Data

Ajay Mandlekar, Fabio Ramos, Byron Boots, Silvio Savarese, Li Fei-Fei, Animesh Garg, Dieter Fox

ICRA 2020

[pdf] [website] [video] [talk]

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Controlling Assistive Robots with Learned Latent Actions

Dylan P. Losey, Krishnan Srinivasan, Ajay Mandlekar, Animesh Garg, Dorsa Sadigh

ICRA 2020

[pdf] [blog] [video]

RoboTurk Real Dataset 

Scaling Robot Supervision to Hundreds of Hours with RoboTurk: Robotic Manipulation Dataset through Human Reasoning and Dexterity

Ajay Mandlekar, Jonathan Booher, Max Spero, Albert Tung, Anchit Gupta, Yuke Zhu, Animesh Garg, Silvio Savarese, Li Fei-Fei

IROS 2019

Best Cognitive Robotics Paper Finalist

[pdf] [website] [blog] [talk]

AC-Teach Figure 

AC-Teach: A Bayesian Actor-Critic Method for Policy Learning with an Ensemble of Suboptimal Teachers

Andrey Kurenkov*, Ajay Mandlekar*, Roberto Martín-Martín, Silvio Savarese, Animesh Garg

CoRL 2019

[pdf] [website] [blog] [talk]

RoboTurk Figure 

RoboTurk: A Crowdsourcing Platform for Robotic Skill Learning through Imitation

Ajay Mandlekar, Yuke Zhu, Animesh Garg, Jonathan Booher, Max Spero, Albert Tung, Julian Gao, John Emmons, Anchit Gupta, Emre Orbay, Silvio Savarese, Li Fei-Fei

CoRL 2018

[pdf] [website] [talk]

ARPL Figure 

Adversarially Robust Policy Learning: Active Construction of Physically-Plausible Perturbations

Ajay Mandlekar*, Yuke Zhu*, Animesh Garg*, Li Fei-Fei, Silvio Savarese

IROS 2017

[pdf] [website] [video]

RSIRL Figure 

Risk-sensitive Inverse Reinforcement Learning via Coherent Risk Models

Anirudha Majumdar, Sumeet Singh, Ajay Mandlekar, Marco Pavone

RSS 2017

[pdf]

Technical Reports

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robosuite: A Modular Simulation Framework and Benchmark for Robot Learning

Yuke Zhu, Josiah Wong, Ajay Mandlekar, Roberto Martin-Martin

Technical Report

[pdf] [website]