| Integrated task and motion planning CR Garrett, R Chitnis, R Holladay, B Kim, T Silver, LP Kaelbling, ... Annual review of control, robotics, and autonomous systems 4 (1), 265-293, 2021 | 591 | 2021 |
| Open x-embodiment: Robotic learning datasets and rt-x models JJ Lim IEEE International Conference on Robotics and Automation, 2024 | 519* | 2024 |
| Socially adaptive path planning in human environments using inverse reinforcement learning B Kim, J Pineau International Journal of Social Robotics 8, 51-66, 2016 | 295 | 2016 |
| Learning from limited demonstrations B Kim, A Farahmand, J Pineau, D Precup Advances in Neural Information Processing Systems 26, 2013 | 147 | 2013 |
| Learning to guide task and motion planning using score-space representation B Kim, Z Wang, LP Kaebling, T Lozano-Perez The International Journal of Robotics Research 28 (7), 2019 | 111 | 2019 |
| Monte carlo tree search in continuous spaces using voronoi optimistic optimization with regret bounds B Kim, K Lee, S Lim, L Kaelbling, T Lozano-Pérez Proceedings of the AAAI Conference on Artificial Intelligence 34 (06), 9916-9924, 2020 | 59 | 2020 |
| Maximum Mean Discrepancy Imitation Learning B Kim, J Pineau Robotics: Science and Systems, 2013 | 59 | 2013 |
| Learning value functions with relational state representations for guiding task-and-motion planning B Kim, L Shimanuki Conference on robot learning, 955-968, 2020 | 58 | 2020 |
| Regret bounds for meta bayesian optimization with an unknown gaussian process prior Z Wang, B Kim, LP Kaelbling Advances in Neural Information Processing Systems 31, 2018 | 54 | 2018 |
| Guiding Search in Continuous State-action Spaces by Learning an Action Sampler from Off-target Search Experience B Kim, LP Kaelbling, T Lozano-Pérez AAAI Conference on Artificial Intelligence, 2018 | 46 | 2018 |
| A long horizon planning framework for manipulating rigid pointcloud objects A Simeonov, Y Du, B Kim, F Hogan, J Tenenbaum, P Agrawal, ... Conference on Robot Learning, 1582-1601, 2021 | 44 | 2021 |
| Open x-embodiment: Robotic learning datasets and rt-x models Q Vuong, S Levine, HR Walke, K Pertsch, A Singh, R Doshi, C Xu, J Luo, ... Towards Generalist Robots: Learning Paradigms for Scalable Skill Acquisition …, 2023 | 36 | 2023 |
| Camps: Learning context-specific abstractions for efficient planning in factored mdps R Chitnis, T Silver, B Kim, L Kaelbling, T Lozano-Perez Conference on robot learning, 64-79, 2021 | 35 | 2021 |
| Representation, learning, and planning algorithms for geometric task and motion planning B Kim, L Shimanuki, LP Kaelbling, T Lozano-Pérez The International Journal of Robotics Research 41 (2), 210-231, 2022 | 31 | 2022 |
| Learning whole-body manipulation for quadrupedal robot S Jeon, M Jung, S Choi, B Kim, J Hwangbo IEEE Robotics and Automation Letters 9 (1), 699-706, 2023 | 30 | 2023 |
| Adversarial actor-critic method for task and motion planning problems using planning experience B Kim, LP Kaelbling, T Lozano-Pérez Proceedings of the AAAI conference on artificial intelligence 33 (01), 8017-8024, 2019 | 26 | 2019 |
| Human-like navigation: Socially adaptive path planning in dynamic environments B Kim, J Pineau RSS 2013 workshop on inverse optimal control and robotic learning from …, 2013 | 13 | 2013 |
| Pre-and post-contact policy decomposition for non-prehensile manipulation with zero-shot sim-to-real transfer M Kim, J Han, J Kim, B Kim 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2023 | 11 | 2023 |
| CORN: Contact-based Object Representation for Nonprehensile Manipulation of General Unseen Objects Y Cho, J Han, Y Cho, B Kim arXiv preprint arXiv:2403.10760, 2024 | 7 | 2024 |
| Generalizing over uncertain dynamics for online trajectory generation B Kim, A Kim, H Dai, L Kaelbling, T Lozano-Perez Robotics Research: Volume 2, 39-55, 2018 | 6 | 2018 |
Leslie Kaelblingcsail.mit.edu의 이메일 확인됨
