Ajay Mandlekar

According to our database, Ajay Mandlekar authored at least 42 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

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

Trans. Mach. Learn. Res., 2024

DexMimicGen: Automated Data Generation for Bimanual Dexterous Manipulation via Imitation Learning.

Zhenyu Jiang, Yuqi Xie, Kevin Lin, Zhenjia Xu, Weikang Wan, Ajay Mandlekar, Linxi Fan, Yuke Zhu

CoRR, 2024

One-Step Diffusion Policy: Fast Visuomotor Policies via Diffusion Distillation.

Zhendong Wang, Zhaoshuo Li, Ajay Mandlekar, Zhenjia Xu, Jiaojiao Fan, Yashraj S. Narang, Linxi Fan, Yuke Zhu, Yogesh Balaji, Mingyuan Zhou, Ming-Yu Liu, Yu Zeng

CoRR, 2024

SkillMimicGen: Automated Demonstration Generation for Efficient Skill Learning and Deployment.

Caelan Reed Garrett, Ajay Mandlekar, Bowen Wen, Dieter Fox

CoRR, 2024

SPIRE: Synergistic Planning, Imitation, and Reinforcement Learning for Long-Horizon Manipulation.

Zihan Zhou, Animesh Garg, Dieter Fox, Caelan Reed Garrett, Ajay Mandlekar

CoRR, 2024

Latent Action Pretraining from Videos.

Seonghyeon Ye, Joel Jang, Byeongguk Jeon, Se June Joo, Jianwei Yang, Baolin Peng, Ajay Mandlekar, Reuben Tan, Yu-Wei Chao, Bill Yuchen Lin, Lars Liden, Kimin Lee, Jianfeng Gao, Luke Zettlemoyer, Dieter Fox, Minjoon Seo

CoRR, 2024

AHA: A Vision-Language-Model for Detecting and Reasoning Over Failures in Robotic Manipulation.

Jiafei Duan, Wilbert Pumacay, Nishanth Kumar, Yi Ru Wang, Shulin Tian, Wentao Yuan, Ranjay Krishna, Dieter Fox, Ajay Mandlekar, Yijie Guo

CoRR, 2024

Deep Generative Models in Robotics: A Survey on Learning from Multimodal Demonstrations.

Julen Urain, Ajay Mandlekar, Yilun Du, Mahi Shafiullah, Danfei Xu, Katerina Fragkiadaki, Georgia Chalvatzaki, Jan Peters

CoRR, 2024

RoboCasa: Large-Scale Simulation of Everyday Tasks for Generalist Robots.

Soroush Nasiriany, Abhiram Maddukuri, Lance Zhang, Adeet Parikh, Aaron Lo, Abhishek Joshi, Ajay Mandlekar, Yuke Zhu

CoRR, 2024

IntervenGen: Interventional Data Generation for Robust and Data-Efficient Robot Imitation Learning.

Ryan Hoque, Ajay Mandlekar, Caelan Reed Garrett, Ken Goldberg, Dieter Fox

CoRR, 2024

Signatures meet dynamic programming: Generalizing Bellman equations for trajectory following.

Motoya Ohnishi, Iretiayo Akinola, Jie Xu, Ajay Mandlekar, Fabio Ramos

Proceedings of the 6th Annual Learning for Dynamics & Control Conference, 2024

Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration.

Abby O'Neill, Abdul Rehman, Abhiram Maddukuri, Abhishek Gupta, Abhishek Padalkar, Abraham Lee, Acorn Pooley, Agrim Gupta, Ajay Mandlekar, Ajinkya Jain, Albert Tung, Alex Bewley, Alexander Herzog, Alex Irpan, Alexander Khazatsky, Anant Rai, Anchit Gupta, Andrew Wang, Anikait Singh, Animesh Garg, Aniruddha Kembhavi, Annie Xie, Anthony Brohan, Antonin Raffin, Archit Sharma, Arefeh Yavary, Arhan Jain, Ashwin Balakrishna, Ayzaan Wahid, Ben Burgess-Limerick, Beomjoon Kim, Bernhard Schölkopf, Blake Wulfe, Brian Ichter, Cewu Lu, Charles Xu, Charlotte Le, Chelsea Finn, Chen Wang, Chenfeng Xu, Cheng Chi, Chenguang Huang, Christine Chan, Christopher Agia, Chuer Pan, Chuyuan Fu, Coline Devin, Danfei Xu, Daniel Morton, Danny Driess, Daphne Chen, Deepak Pathak, Dhruv Shah, Dieter Büchler, Dinesh Jayaraman, Dmitry Kalashnikov, Dorsa Sadigh, Edward Johns, Ethan Paul Foster, Fangchen Liu, Federico Ceola, Fei Xia, Feiyu Zhao, Freek Stulp, Gaoyue Zhou, Gaurav S. Sukhatme, Gautam Salhotra, Ge Yan, Gilbert Feng, Giulio Schiavi, Glen Berseth, Gregory Kahn, Guanzhi Wang, Hao Su, Haoshu Fang, Haochen Shi, Henghui Bao, Heni Ben Amor, Henrik I. Christensen, Hiroki Furuta, Homer Walke, Hongjie Fang, Huy Ha, Igor Mordatch, Ilija Radosavovic, Isabel Leal, Jacky Liang, Jad Abou-Chakra, Jaehyung Kim, Jaimyn Drake, Jan Peters, Jan Schneider, Jasmine Hsu, Jeannette Bohg, Jeffrey Bingham, Jeffrey Wu, Jensen Gao, Jiaheng Hu, Jiajun Wu, Jialin Wu, Jiankai Sun, Jianlan Luo, Jiayuan Gu, Jie Tan, Jihoon Oh, Jimmy Wu, Jingpei Lu, Jingyun Yang, Jitendra Malik, João Silvério, Joey Hejna, Jonathan Booher, Jonathan Tompson, Jonathan Yang, Jordi Salvador, Joseph J. Lim, Junhyek Han, Kaiyuan Wang, Kanishka Rao, Karl Pertsch, Karol Hausman, Keegan Go, Keerthana Gopalakrishnan, Ken Goldberg, Kendra Byrne, Kenneth Oslund, Kento Kawaharazuka, Kevin Black, Kevin Lin, Kevin Zhang, Kiana Ehsani, Kiran Lekkala, Kirsty Ellis, Krishan Rana, Krishnan Srinivasan, Kuan Fang, Kunal Pratap Singh, Kuo-Hao Zeng, Kyle Hatch, Kyle Hsu, Laurent Itti, Lawrence Yunliang Chen, Lerrel Pinto, Li Fei-Fei, Liam Tan, Linxi Jim Fan, Lionel Ott, Lisa Lee, Luca Weihs, Magnum Chen, Marion Lepert, Marius Memmel, Masayoshi Tomizuka, Masha Itkina, Mateo Guaman Castro, Max Spero, Maximilian Du, Michael Ahn, Michael C. Yip, Mingtong Zhang, Mingyu Ding, Minho Heo, Mohan Kumar Srirama, Mohit Sharma, Moo Jin Kim, Naoaki Kanazawa, Nicklas Hansen, Nicolas Heess, Nikhil J. Joshi, Niko Sünderhauf, Ning Liu, Norman Di Palo, Nur Muhammad (Mahi) Shafiullah, Oier Mees, Oliver Kroemer, Osbert Bastani, Pannag R. Sanketi, Patrick Tree Miller, Patrick Yin, Paul Wohlhart, Peng Xu, Peter David Fagan, Peter Mitrano, Pierre Sermanet, Pieter Abbeel, Priya Sundaresan, Qiuyu Chen, Quan Vuong, Rafael Rafailov, Ran Tian, Ria Doshi, Roberto Martín-Martín, Rohan Baijal, Rosario Scalise, Rose Hendrix, Roy Lin, Runjia Qian, Ruohan Zhang, Russell Mendonca, Rutav Shah, Ryan Hoque, Ryan Julian, Samuel Bustamante, Sean Kirmani, Sergey Levine, Shan Lin, Sherry Moore, Shikhar Bahl, Shivin Dass, Shubham D. Sonawani, Shuran Song, Sichun Xu, Siddhant Haldar, Siddharth Karamcheti, Simeon Adebola, Simon Guist, Soroush Nasiriany, Stefan Schaal, Stefan Welker, Stephen Tian, Subramanian Ramamoorthy, Sudeep Dasari, Suneel Belkhale, Sungjae Park, Suraj Nair, Suvir Mirchandani, Takayuki Osa, Tanmay Gupta, Tatsuya Harada, Tatsuya Matsushima, Ted Xiao, Thomas Kollar, Tianhe Yu, Tianli Ding, Todor Davchev, Tony Z. Zhao, Travis Armstrong, Trevor Darrell, Trinity Chung, Vidhi Jain, Vincent Vanhoucke, Wei Zhan, Wenxuan Zhou, Wolfram Burgard, Xi Chen, Xiaolong Wang, Xinghao Zhu, Xinyang Geng, Xiyuan Liu, Liangwei Xu, Xuanlin Li, Yao Lu, Yecheng Jason Ma, Yejin Kim, Yevgen Chebotar, Yifan Zhou, Yifeng Zhu, Yilin Wu, Ying Xu, Yixuan Wang, Yonatan Bisk, Yoonyoung Cho, Youngwoon Lee, Yuchen Cui, Yue Cao, Yueh-Hua Wu, Yujin Tang, Yuke Zhu, Yunchu Zhang, Yunfan Jiang, Yunshuang Li, Yunzhu Li, Yusuke Iwasawa, Yutaka Matsuo, Zehan Ma, Zhuo Xu, Zichen Jeff Cui, Zichen Zhang, Zipeng Lin

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

2023

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, Ritvik Singh, Yunrong Guo, Hammad Mazhar, Ajay Mandlekar, Buck Babich, Gavriel State, Marco Hutter, Animesh Garg

IEEE Robotics Autom. Lett., June, 2023

NOD-TAMP: Multi-Step Manipulation Planning with Neural Object Descriptors.

Shuo Cheng, Caelan Reed Garrett, Ajay Mandlekar, Danfei Xu

CoRR, 2023

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

CoRR, 2023

Active Task Randomization: Learning Robust Skills via Unsupervised Generation of Diverse and Feasible Tasks.

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

IROS, 2023

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

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

Proceedings of the Conference on Robot Learning, 2023

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

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

Proceedings of the Conference on Robot Learning, 2023

Imitating Task and Motion Planning with Visuomotor Transformers.

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

Proceedings of the Conference on Robot Learning, 2023

2022

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

CoRR, 2022

Learning latent actions to control assistive robots.

Dylan P. Losey, Hong Jun Jeon, Mengxi Li, Krishnan Srinivasan, Ajay Mandlekar, Animesh Garg, Jeannette Bohg, Dorsa Sadigh

Auton. Robots, 2022

MoCoDA: Model-based Counterfactual Data Augmentation.

Silviu Pitis, Elliot Creager, Ajay Mandlekar, Animesh Garg

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

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

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

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

Soroush Nasiriany, Tian Gao, Ajay Mandlekar, Yuke Zhu

Proceedings of the Conference on Robot Learning, 2022

2021

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

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

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

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Learning Multi-Arm Manipulation Through Collaborative Teleoperation.

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

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

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

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

S4RL: Surprisingly Simple Self-Supervision for Offline Reinforcement Learning in Robotics.

Samarth Sinha, Ajay Mandlekar, Animesh Garg

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

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

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

2020

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

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

CoRR, 2020

robosuite: A Modular Simulation Framework and Benchmark for Robot Learning.

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

CoRR, 2020

Learning to Generalize Across Long-Horizon Tasks from Human Demonstrations.

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

CoRR, 2020

GTI: Learning to Generalize across Long-Horizon Tasks from Human Demonstrations.

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

Proceedings of the Robotics: Science and Systems XVI, 2020

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

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

Controlling Assistive Robots with Learned Latent Actions.

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

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

2019

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

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

CoRR, 2019

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

Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019

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

Proceedings of the 3rd Annual Conference on Robot Learning, 2019

2018

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

Proceedings of the 2nd Annual Conference on Robot Learning, 2018

2017

Risk-sensitive Inverse Reinforcement Learning via Coherent Risk Models.

Anirudha Majumdar, Sumeet Singh, Ajay Mandlekar, Marco Pavone

Proceedings of the Robotics: Science and Systems XIII, 2017

Adversarially Robust Policy Learning: Active construction of physically-plausible perturbations.

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

Proceedings of the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2017