Planning-Augmented Hierarchical Reinforcement Learning R Gieselmann, FT Pokorny IEEE Robotics and Automation Letters 6 (3), 5097-5104, 2021 | 24 | 2021 |
Experience-based heuristic search: Robust motion planning with deep Q-learning J Bernhard, R Gieselmann, K Esterle, A Knoll 2018 21st International conference on intelligent transportation systems …, 2018 | 24 | 2018 |
Reform: A robot learning sandbox for deformable linear object manipulation R Laezza, R Gieselmann, FT Pokorny, Y Karayiannidis 2021 IEEE International Conference on Robotics and Automation (ICRA), 4717-4723, 2021 | 20 | 2021 |
Latent Planning via Expansive Tree Search R Gieselmann, FT Pokorny Advances in Neural Information Processing Systems, 2022 | 5 | 2022 |
Expansive Latent Planning for Sparse Reward Offline Reinforcement Learning R Gieselmann, FT Pokorny Conference on Robot Learning, 1-22, 2023 | 2 | 2023 |
Standard Deep Generative Models for Density Estimation in Configuration Spaces: A Study of Benefits, Limits and Challenges R Gieselmann, FT Pokorny 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2020 | 2 | 2020 |
Fast-dRRT*: Efficient Multi-Robot Motion Planning for Automated Industrial Manufacturing A Solano, A Sieverling, R Gieselmann, A Orthey arXiv preprint arXiv:2309.10665, 2023 | 1 | 2023 |
An Expansive Latent Planner for Long-horizon Visual Offline Reinforcement Learning R Gieselmann, FT Pokorny RSS 2023 Workshop on Learning for Task and Motion Planning, 2023 | 1 | 2023 |
Synergies between Policy Learning and Sampling-based Planning R Gieselmann KTH Royal Institute of Technology, 2024 | | 2024 |
DLO@Scale - A Large-Scale Meta Dataset for Learning Non-Rigid Object Pushing Dynamics R Gieselmann, A Longhini, A Reichlin, D Kragic, FT Pokorny NeurIPS 2021 - Workshop on Physical Reasoning and Inductive Biases for the …, 2021 | | 2021 |
Presenting ReForm, a Robot Learning Sandbox for Deformable Linear Object Manipulation R Laezza, R Gieselmann, FT Pokorny, Y Karayiannidis | | |