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Robert Gieselmann
Robert Gieselmann
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Title
Cited by
Cited by
Year
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
232018
Planning-Augmented Hierarchical Reinforcement Learning
R Gieselmann, FT Pokorny
IEEE Robotics and Automation Letters 6 (3), 5097-5104, 2021
212021
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
192021
Latent Planning via Expansive Tree Search
R Gieselmann, FT Pokorny
Advances in Neural Information Processing Systems, 2022
52022
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
22020
Expansive Latent Planning for Sparse Reward Offline Reinforcement Learning
R Gieselmann, FT Pokorny
Conference on Robot Learning, 1-22, 2023
12023
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
12023
Synergies between Policy Learning and Sampling-based Planning
R Gieselmann
KTH Royal Institute of Technology, 2024
2024
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
2023
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
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