| Voyager: An open-ended embodied agent with large language models G Wang, Y Xie, Y Jiang, A Mandlekar, C Xiao, Y Zhu, L Fan, ... arXiv preprint arXiv:2305.16291, 2023 | 1631 | 2023 |
| Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration0 A O’Neill, A Rehman, A Maddukuri, A Gupta, A Padalkar, A Lee, A Pooley, ... 2024 IEEE International Conference on Robotics and Automation (ICRA), 6892-6903, 2024 | 919 | 2024 |
| What matters in learning from offline human demonstrations for robot manipulation A Mandlekar, D Xu, J Wong, S Nasiriany, C Wang, R Kulkarni, L Fei-Fei, ... arXiv preprint arXiv:2108.03298, 2021 | 758 | 2021 |
| robosuite: A modular simulation framework and benchmark for robot learning Y Zhu, J Wong, A Mandlekar, R Martín-Martín, A Joshi, S Nasiriany, Y Zhu arXiv preprint arXiv:2009.12293, 2020 | 657 | 2020 |
| Minedojo: Building open-ended embodied agents with internet-scale knowledge L Fan, G Wang, Y Jiang, A Mandlekar, Y Yang, H Zhu, A Tang, DA Huang, ... Advances in Neural Information Processing Systems 35, 18343-18362, 2022 | 578 | 2022 |
| Roboturk: A crowdsourcing platform for robotic skill learning through imitation A Mandlekar, Y Zhu, A Garg, J Booher, M Spero, A Tung, J Gao, ... Conference on Robot Learning, 879-893, 2018 | 391 | 2018 |
| Orbit: A unified simulation framework for interactive robot learning environments M Mittal, C Yu, Q Yu, J Liu, N Rudin, D Hoeller, JL Yuan, R Singh, Y Guo, ... IEEE Robotics and Automation Letters 8 (6), 3740-3747, 2023 | 295 | 2023 |
| Gr00t n1: An open foundation model for generalist humanoid robots J Bjorck, F Castañeda, N Cherniadev, X Da, R Ding, L Fan, Y Fang, D Fox, ... arXiv preprint arXiv:2503.14734, 2025 | 294 | 2025 |
| Mimicgen: A data generation system for scalable robot learning using human demonstrations A Mandlekar, S Nasiriany, B Wen, I Akinola, Y Narang, L Fan, Y Zhu, ... arXiv preprint arXiv:2310.17596, 2023 | 244 | 2023 |
| Adversarially robust policy learning: Active construction of physically-plausible perturbations A Mandlekar, Y Zhu, A Garg, L Fei-Fei, S Savarese 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2017 | 241 | 2017 |
| Learning to generalize across long-horizon tasks from human demonstrations A Mandlekar, D Xu, R Martín-Martín, S Savarese, L Fei-Fei arXiv preprint arXiv:2003.06085, 2020 | 208 | 2020 |
| Robocasa: Large-scale simulation of everyday tasks for generalist robots S Nasiriany, A Maddukuri, L Zhang, A Parikh, A Lo, A Joshi, A Mandlekar, ... arXiv preprint arXiv:2406.02523, 2024 | 201 | 2024 |
| Iris: Implicit reinforcement without interaction at scale for learning control from offline robot manipulation data A Mandlekar, F Ramos, B Boots, S Savarese, L Fei-Fei, A Garg, D Fox 2020 IEEE International Conference on Robotics and Automation (ICRA), 4414-4420, 2020 | 169 | 2020 |
| S4rl: Surprisingly simple self-supervision for offline reinforcement learning in robotics S Sinha, A Mandlekar, A Garg Conference on Robot Learning, 907-917, 2022 | 163 | 2022 |
| Latent action pretraining from videos S Ye, J Jang, B Jeon, S Joo, J Yang, B Peng, A Mandlekar, R Tan, ... arXiv preprint arXiv:2410.11758, 2024 | 147 | 2024 |
| Scaling robot supervision to hundreds of hours with roboturk: Robotic manipulation dataset through human reasoning and dexterity A Mandlekar, J Booher, M Spero, A Tung, A Gupta, Y Zhu, A Garg, ... 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2019 | 124 | 2019 |
| Human-in-the-loop imitation learning using remote teleoperation A Mandlekar, D Xu, R Martín-Martín, Y Zhu, L Fei-Fei, S Savarese arXiv preprint arXiv:2012.06733, 2020 | 119 | 2020 |
| Controlling assistive robots with learned latent actions DP Losey, K Srinivasan, A Mandlekar, A Garg, D Sadigh 2020 IEEE International Conference on Robotics and Automation (ICRA), 378-384, 2020 | 107 | 2020 |
| Gavriel State, Marco Hutter, and Animesh Garg. Orbit: A unified simulation framework for interactive robot learning environments M Mittal, C Yu, Q Yu, J Liu, N Rudin, D Hoeller, JL Yuan, R Singh, Y Guo, ... IEEE Robotics and Automation Letters 8 (6), 3740-3747, 2023 | 106 | 2023 |
| Deep affordance foresight: Planning through what can be done in the future D Xu, A Mandlekar, R Martín-Martín, Y Zhu, S Savarese, L Fei-Fei 2021 IEEE international conference on robotics and automation (ICRA), 6206-6213, 2021 | 104 | 2021 |
