Recent News

  • [December 2020] We recently extended RoboTurk to enable human-in-the-loop teleoperation and developed Intervention Weighted Regression, a simple and effective algorithm to learn from such interventions. We showcase results on two challenging contact-rich manipulation tasks requiring precision to solve.

  • [December 2020] We recently extended RoboTurk to enable multi-user collaborative teleoperation on challenging multi-arm tasks. We collected datasets on novel two-arm and three-arm tasks and developed a residual policy framework to address the problem of learning from multi-user demonstration data.

  • [December 2020] Check out our new preprint on Deep Affordance Foresight, a new model that extends the classical definition of affordance to enable long-horizon planning.

  • [September 2020] We released robosuite v1.0, a modular simulation framework and benchmark for robot learning.



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

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

Under Review

[pdf] [website] [video]


Learning Multi-Arm Manipulation Through Collaborative Teleoperation

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

Under Review

[pdf] [website] [video]


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

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

Under Review

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


robosuite: A Modular Simulation Framework and Benchmark for Robot Learning

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

Technical Report

[pdf] [website]


Learning to Generalize Across Long-Horizon Tasks from Human Demonstrations

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

RSS 2020

[pdf] [website] [video]


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]


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

Best Cognitive Robotics Paper Finalist

IROS 2019

[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 Martin-Martin, 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