Követés
Puze Liu
Puze Liu
German Research Center for AI (DFKI)
E-mail megerősítve itt: dfki.de - Kezdőlap
Cím
Hivatkozott rá
Hivatkozott rá
Év
Robot reinforcement learning on the constraint manifold
P Liu, D Tateo, HB Ammar, J Peters
Conference on Robot Learning, 1357-1366, 2022
532022
Regularized deep signed distance fields for reactive motion generation
P Liu, K Zhang, D Tateo, S Jauhri, J Peters, G Chalvatzaki
2022 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2022
352022
Composable Energy Policies for Reactive Motion Generation and Reinforcement Learning
J Urain, A Li, P Liu, C D'Eramo, J Peters
Robotics: Science and Systems (RSS), 2021
302021
Efficient and reactive planning for high speed robot air hockey
P Liu, D Tateo, H Bou-Ammar, J Peters
RSJ International Conference on Intelligent Robots and Systems (IROS), 586-593, 2021
262021
Fast kinodynamic planning on the constraint manifold with deep neural networks
P Kicki, P Liu, D Tateo, H Bou-Ammar, K Walas, P Skrzypczyński, J Peters
IEEE Transactions on Robotics, 2023
202023
Safe reinforcement learning of dynamic high-dimensional robotic tasks: navigation, manipulation, interaction
P Liu, K Zhang, D Tateo, S Jauhri, Z Hu, J Peters, G Chalvatzaki
2023 IEEE International Conference on Robotics and Automation (ICRA), 9449-9456, 2023
192023
Efficient and Reactive Planning for High Speed Robot Air Hockey
P Liu, D Tateo, H Bou-Ammar, J Peters
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2021
152021
Ros-llm: A ros framework for embodied ai with task feedback and structured reasoning
CE Mower, Y Wan, H Yu, A Grosnit, J Gonzalez-Billandon, M Zimmer, ...
arXiv preprint arXiv:2406.19741, 2024
82024
Safe Reinforcement Learning on the Constraint Manifold: Theory and Applications
P Liu, H Bou-Ammar, J Peters, D Tateo
arXiv preprint arXiv:2404.09080, 2024
62024
Dimensionality reduction and prioritized exploration for policy search
M Memmel, P Liu, D Tateo, J Peters
International Conference on Artificial Intelligence and Statistics, 2134-2157, 2022
42022
Bridging the gap between learning-to-plan, motion primitives and safe reinforcement learning
P Kicki, D Tateo, P Liu, J Guenster, J Peters, K Walas
arXiv preprint arXiv:2408.14063, 2024
22024
Energy-based Contact Planning under Uncertainty for Robot Air Hockey
J Jankowski, A Marić, P Liu, D Tateo, J Peters, S Calinon
arXiv preprint arXiv:2407.03705, 2024
12024
A Retrospective on the Robot Air Hockey Challenge: Benchmarking Robust, Reliable, and Safe Learning Techniques for Real-world Robotics
P Liu, J Günster, N Funk, S Gröger, D Chen, H Bou Ammar, J Jankowski, ...
Advances in Neural Information Processing Systems 37, 9690-9726, 2025
2025
Adaptive Control Based Friction Estimation for Tracking Control of Robot Manipulators
J Huang, D Tateo, P Liu, J Peters
IEEE Robotics and Automation Letters, 2025
2025
Handling Long-Term Safety and Uncertainty in Safe Reinforcement Learning
J Günster, P Liu, J Peters, D Tateo
arXiv preprint arXiv:2409.12045, 2024
2024
ROSCOM: Robust Safe Reinforcement Learning on Stochastic Constraint Manifolds
S Gu, P Liu, A Kshirsagar, G Chen, J Peters, A Knoll
IEEE Transactions on Automation Science and Engineering, 2024
2024
ReDSDF: Regularized Deep Signed Distance Fields for Robotics
P Liu, K Zhang, D Tateo, S Jauhri, J Peters, G Chalvatzaki
2022
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