Intelligent Mobile Manipulation Lab
2021

Integrated task and motion planning.
Caelan Reed Garrett, Rohan Chitnis, Rachel Holladay, Beomjoon Kim, Tom Silver, Leslie Pack Kaelbling, Tomás Lozano-Pérez.
Annual Review of Control, Robotics, and Autonomous Systems, 2021. [pdf] [arXiv]

2020

A Long Horizon Planning Framework for Manipulating Rigid Pointcloud Objects.
Anthony Simeonov, Yilun Du, Beomjoon Kim, Francois Hogan, Joshua Tenenbaum, Pulkit Agrawal, Alberto Rodriguez.
Conference on Robot Learning (CoRL), 2020. [arXiv] [project page] [video]

CAMPs: Learning Context-Specific Abstractions for Efficient Planning in Factored MDPs.
Rohan Chitnis*, Tom Silver*, Beomjoon Kim, Leslie Pack Kaelbling, Tomás Lozano-Pérez
Conference on Robot Learning (CoRL), 2020. Plenary talk (top 12% of accepted papers). [pdf] [video]

Monte Carlo Tree Search in continuous spaces using Voronoi optimistic optimization with regret bounds.
Beomjoon Kim, Kyungjae Lee, Sungbin Lim, Leslie Pack Kaelbling, Tomas Lozano-Perez.
AAAI Conference on Artificial Intelligence (AAAI), 2020. Oral (top 6% of accepted papers). [pdf]

2019

Learning to guide task and motion planning using score-space representation.
Beomjoon Kim, Zi Wang, Leslie Pack Kaelbling, Tomas Lozano-Perez.
International Journal of Robotics Research, 2019. [doi] [arXiv]

Learning value functions with relational state representations for guiding task-and-motion planning.
Beomjoon Kim, Luke Shimanuki
Conference on Robot Learning (CoRL), 2019. [pdf] [appendix]

Adversarial actor-critic method for task and motion planning problems using planning experience.
Beomjoon Kim, Leslie Pack Kaelbling, Tomas Lozano-Perez
AAAI Conference on Artificial Intelligence (AAAI), 2019. Oral (top 6% of accepted papers). [pdf] [appendix]

2018

Regret bounds for meta Bayesian optimization with an unknown Gaussian process prior.
Zi Wang*, Beomjoon Kim*, Leslie Pack Kaelbling
Neural Information Processing Systems (NeurIPS), 2018. Spotlight (top 3.5% of accepted papers). [pdf]

Guiding search in continuous state-action spaces by learning an action sampler from off-target search experience.
Beomjoon Kim, Leslie Pack Kaelbling, Tomas Lozano-Perez
AAAI Conference on Artificial Intelligence (AAAI), 2018. Oral (top 6% of accepted papers). [pdf]

2017

Learning to guide task and motion planning using score-space representation.
Beomjoon Kim, Leslie Pack Kaelbling, Tomas Lozano-Perez
International Conference on Robotics and Automation (ICRA), 2017. Winner of Best Cognitive Robotics Paper Award. [pdf]

Prior to 2016

Generalizing over uncertain dynamics for on-line trajectory generation.
Beomjoon Kim, Leslie Pack Kaelbling, Tomas Lozano-Perez
International Symposium of Robotics Research (ISRR), 2015. [pdf]

Learning from limited demonstrations.
Beomjoon Kim, Amir-massoud Farahmand, Doina Precup, Joelle Pineau.
Neural Information Processing Systems (NeurIPS), 2013. Spotlight (top 4% of accepted papers). [pdf]

Maximum mean discrepancy imitation learning.
Beomjoon Kim, Joelle Pineau.
Robotics: Science and Systems (RSS), 2013. [pdf]