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 | 433 | 2021 |
Socially adaptive path planning in human environments using inverse reinforcement learning B Kim, J Pineau International Journal of Social Robotics 8, 51-66, 2016 | 270 | 2016 |
Learning from limited demonstrations B Kim, A Farahmand, J Pineau, D Precup Advances in Neural Information Processing Systems 26, 2013 | 136 | 2013 |
Open x-embodiment: Robotic learning datasets and rt-x models A Padalkar, A Pooley, A Jain, A Bewley, A Herzog, A Irpan, A Khazatsky, ... arXiv preprint arXiv:2310.08864, 2023 | 130 | 2023 |
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 | 101 | 2019 |
Maximum Mean Discrepancy Imitation Learning B Kim, J Pineau Robotics: Science and Systems, 2013 | 57 | 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 | 46 | 2020 |
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 | 46 | 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 | 43 | 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 | 41 | 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 | 35 | 2021 |
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 | 31 | 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 | 27 | 2022 |
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 | 23 | 2019 |
Open X-Embodiment: Robotic learning datasets and RT-X models OXE Collaboration, A Padalkar, A Pooley, A Jain, A Bewley, A Herzog, ... CoRR, abs/2310.08864, 2023 | 20 | 2023 |
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 | 12 | 2023 |
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 | 12 | 2013 |
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 | 9 | 2023 |
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 | 5 | 2023 |
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 | 5 | 2018 |