|
PRESTO: Fast motion planning using diffusion models based on key-configuration environment representation.
Mingyo Seo, Yoonyoung Cho, Yoonchang Sung, Peter Stone, Yuke Zhu, Beomjoon Kim.
International Conference on Robotics and Automation (ICRA), 2025.
[pdf]
Prime the Search: Using Large Language Models for Guiding Geometric Task and Motion Planning by Warm-starting Tree Search.
Dongryung Lee*, Sejune Joo*, Kimin Lee, Beomjoon Kim.
International Journal of Robotics Research (IJRR), 2025.
[pdf]
CORN: Contact-based Object Representation for Nonprehensile Manipulation of General Unseen Objects
Yoonyoung Cho, Junhyek Han, Yoontae Cho, Beomjoon Kim
International Conference on Learning Representations (ICLR), 2024.
[pdf]
[video]
[project page]
An Intuitive Multi-Frequency Feature Representation for SO(3)-Equivariant Networks
Dongwon Son, Jaehyung Kim, Sanghyeon Son, Beomjoon Kim
International Conference on Learning Representations (ICLR), 2024.
[pdf]
Open X-Embodiment: robotic learning datasets and RT-X models
Open X-Embodiment Collaboration
International Conference on Robotics and Automation (ICRA), 2023.
[pdf]
Learning whole-body manipulation for quadrupedal robot
Seunghun Jeon, Moonkyu Jung, Suyoung Choi, Beomjoon Kim (co-corresponding author), Jemin Hwangbo
Robotics and Automation Letters (RA-L), 2023.
[pdf]
[video]
Preference learning for guiding the tree search in continuous POMDPs
Jiyong Ahn, Sanghyeon Son, Dongryung Lee, Jisu Han, Dongwon Son, and Beomjoon Kim.
Conference on Robot Learnining (CoRL), 2023.
[pdf]
[project page]
Pre- and Post-Contact Policy Decomposition for Non-Prehensile Manipulation with Sim-to-Real Transfer.
Minchan Kim, Junhyek Han, Jaehyung Kim, and Beomjoon Kim.
International Conference on Intelligent Robots and Systems (IROS), 2023.
[pdf]
[project page]
Local object crop collision network for efficient simulation of non-convex objects in GPU-based simulators.
Dongwon Son, Beomjoon Kim.
Robotics: Science and Systems (RSS), 2023.
[pdf]
[project page]
Ohm^2: Optimal hierarchical planner for object search in large environments via mobile manipulation
Yoonyoung Cho*, Donghoon Shin*, Beomjoon Kim.
International Conference on Intelligent Robots and Systems (IROS), 2022.
[pdf]
Representation, learning, and planning algorithms for geometric task and motion planning
Beomjoon Kim, Luke Shimanuki, Leslie Pack Kaelbling, Tomás Lozano-Pérez.
International Journal of Robotics Research, 2021.
[doi]
[arXiv]
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]
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]
[appendix]
Learning to guide task and motion planning using score-space
representation.
Beomjoon Kim, Zi Wang, Leslie Pack Kaelbling, Tomás Lozano-Pérez.
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, Tomás Lozano-Pérez
AAAI Conference on Artificial Intelligence (AAAI), 2019.
Oral (top 6% of accepted papers).
[pdf]
[appendix]
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, Tomás Lozano-Pérez
AAAI Conference on Artificial Intelligence (AAAI), 2018.
Oral (top 6% of accepted papers).
[pdf]
Learning to guide task and motion planning using score-space representation.
Beomjoon Kim, Leslie Pack Kaelbling, Tomás Lozano-Pérez
International Conference on Robotics and Automation (ICRA), 2017.
Best Cognitive Robotics Paper award.
[pdf]
Socially adaptive path planning in human environments using inverse reinforcement learning .
Beomjoon Kim, Joelle Pineau
International Journal of Social Robotics, 2016.
[pdf]
Generalizing over uncertain dynamics for on-line trajectory generation.
Beomjoon Kim, Leslie Pack Kaelbling, Tomás Lozano-Pérez
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]
|
