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ORCIDDavide Tateo
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- affiliation: TU Darmstadt, Germany
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2020 – today
- 2024
[j7]Felix Herrmann, Sebastian Zach, Jacopo Banfi, Jan Peters, Georgia Chalvatzaki, Davide Tateo:
Safe and Efficient Path Planning Under Uncertainty via Deep Collision Probability Fields. IEEE Robotics Autom. Lett. 9(11): 9327-9334 (2024)- [j6]Piotr Kicki
, Puze Liu, Davide Tateo, Haitham Bou-Ammar, Krzysztof Walas, Piotr Skrzypczynski, Jan Peters:
Fast Kinodynamic Planning on the Constraint Manifold With Deep Neural Networks. IEEE Trans. Robotics 40: 277-297 (2024) - [c15]Firas Al-Hafez, Guoping Zhao, Jan Peters, Davide Tateo:
Time-Efficient Reinforcement Learning with Stochastic Stateful Policies. ICLR 2024 - [i28]Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters:
Sharing Knowledge in Multi-Task Deep Reinforcement Learning. CoRR abs/2401.09561 (2024) - [i27]Puze Liu, Haitham Bou-Ammar, Jan Peters, Davide Tateo:
Safe Reinforcement Learning on the Constraint Manifold: Theory and Applications. CoRR abs/2404.09080 (2024) - [i26]Christopher E. Mower, Yuhui Wan, Hongzhan Yu, Antoine Grosnit, Jonas Gonzalez-Billandon, Matthieu Zimmer, Jinlong Wang, Xinyu Zhang, Yao Zhao, Anbang Zhai, Puze Liu, Davide Tateo, Cesar Cadena, Marco Hutter, Jan Peters, Guangjian Tian, Yuzheng Zhuang, Kun Shao, Xingyue Quan, Jianye Hao, Jun Wang, Haitham Bou-Ammar:
ROS-LLM: A ROS framework for embodied AI with task feedback and structured reasoning. CoRR abs/2406.19741 (2024) - [i25]Julius Jankowski, Ante Maric, Puze Liu, Davide Tateo, Jan Peters, Sylvain Calinon:
Energy-based Contact Planning under Uncertainty for Robot Air Hockey. CoRR abs/2407.03705 (2024) - [i24]Henri-Jacques Geiß, Firas Al-Hafez, Andre Seyfarth, Jan Peters, Davide Tateo:
Exciting Action: Investigating Efficient Exploration for Learning Musculoskeletal Humanoid Locomotion. CoRR abs/2407.11658 (2024) - [i23]Piotr Kicki, Davide Tateo, Puze Liu, Jonas Guenster, Jan Peters, Krzysztof Walas:
Bridging the gap between Learning-to-plan, Motion Primitives and Safe Reinforcement Learning. CoRR abs/2408.14063 (2024) - [i22]Felix Herrmann, Sebastian Zach, Jacopo Banfi, Jan Peters, Georgia Chalvatzaki, Davide Tateo:
Safe and Efficient Path Planning under Uncertainty via Deep Collision Probability Fields. CoRR abs/2409.04306 (2024) - [i21]Junning Huang, Davide Tateo, Puze Liu, Jan Peters:
Adaptive Control based Friction Estimation for Tracking Control of Robot Manipulators. CoRR abs/2409.05054 (2024) - [i20]Nico Bohlinger, Grzegorz Czechmanowski, Maciej Krupka, Piotr Kicki, Krzysztof Walas, Jan Peters, Davide Tateo:
One Policy to Run Them All: an End-to-end Learning Approach to Multi-Embodiment Locomotion. CoRR abs/2409.06366 (2024) - [i19]Jonas Guenster, Puze Liu, Jan Peters, Davide Tateo:
Handling Long-Term Safety and Uncertainty in Safe Reinforcement Learning. CoRR abs/2409.12045 (2024) - 2023
- [j5]Filip Bjelonic, Joonho Lee, Philip Arm, Dhionis V. Sako, Davide Tateo, Jan Peters, Marco Hutter:
Learning-Based Design and Control for Quadrupedal Robots With Parallel-Elastic Actuators. IEEE Robotics Autom. Lett. 8(3): 1611-1618 (2023) - [c14]Firas Al-Hafez, Davide Tateo, Oleg Arenz, Guoping Zhao, Jan Peters:
LS-IQ: Implicit Reward Regularization for Inverse Reinforcement Learning. ICLR 2023 - [c13]Puze Liu, Kuo Zhang, Davide Tateo, Snehal Jauhri, Zhiyuan Hu, Jan Peters, Georgia Chalvatzaki:
Safe Reinforcement Learning of Dynamic High-Dimensional Robotic Tasks: Navigation, Manipulation, Interaction. ICRA 2023: 9449-9456 - [i18]Filip Bjelonic, Joonho Lee, Philip Arm, Dhionis V. Sako, Davide Tateo, Jan Peters, Marco Hutter:
Learning-based Design and Control for Quadrupedal Robots with Parallel-Elastic Actuators. CoRR abs/2301.03509 (2023) - [i17]Piotr Kicki, Puze Liu, Davide Tateo, Haitham Bou-Ammar, Krzysztof Walas, Piotr Skrzypczynski, Jan Peters:
Fast Kinodynamic Planning on the Constraint Manifold with Deep Neural Networks. CoRR abs/2301.04330 (2023) - [i16]Firas Al-Hafez, Davide Tateo, Oleg Arenz, Guoping Zhao, Jan Peters:
LS-IQ: Implicit Reward Regularization for Inverse Reinforcement Learning. CoRR abs/2303.00599 (2023) - [i15]Firas Al-Hafez, Guoping Zhao, Jan Peters, Davide Tateo:
LocoMuJoCo: A Comprehensive Imitation Learning Benchmark for Locomotion. CoRR abs/2311.02496 (2023) - [i14]Firas Al-Hafez, Guoping Zhao, Jan Peters, Davide Tateo:
Time-Efficient Reinforcement Learning with Stochastic Stateful Policies. CoRR abs/2311.04082 (2023) - [i13]Luca Lach, Robert Haschke, Davide Tateo, Jan Peters, Helge J. Ritter, Júlia Borràs Sol, Carme Torras:
Towards Transferring Tactile-based Continuous Force Control Policies from Simulation to Robot. CoRR abs/2311.07245 (2023) - 2022
- [j4]Simone Parisi, Davide Tateo, Maximilian Hensel, Carlo D'Eramo, Jan Peters, Joni Pajarinen:
Long-Term Visitation Value for Deep Exploration in Sparse-Reward Reinforcement Learning. Algorithms 15(3): 81 (2022) - [j3]Riad Akrour, Davide Tateo, Jan Peters:
Continuous Action Reinforcement Learning From a Mixture of Interpretable Experts. IEEE Trans. Pattern Anal. Mach. Intell. 44(10): 6795-6806 (2022) - [j2]Julen Urain, Davide Tateo, Jan Peters:
Learning Stable Vector Fields on Lie Groups. IEEE Robotics Autom. Lett. 7(4): 12569-12576 (2022) - [c12]Marius Memmel, Puze Liu, Davide Tateo, Jan Peters:
Dimensionality Reduction and Prioritized Exploration for Policy Search. AISTATS 2022: 2134-2157 - [c11]Puze Liu, Kuo Zhang, Davide Tateo, Snehal Jauhri, Jan Peters, Georgia Chalvatzaki:
Regularized Deep Signed Distance Fields for Reactive Motion Generation. IROS 2022: 6673-6680 - [i12]Puze Liu, Kuo Zhang, Davide Tateo, Snehal Jauhri, Jan Peters, Georgia Chalvatzaki:
Regularized Deep Signed Distance Fields for Reactive Motion Generation. CoRR abs/2203.04739 (2022) - [i11]Marius Memmel, Puze Liu, Davide Tateo, Jan Peters:
Dimensionality Reduction and Prioritized Exploration for Policy Search. CoRR abs/2203.04791 (2022) - [i10]Davide Tateo, Davide Antonio Cucci, Matteo Matteucci, Andrea Bonarini:
Object Structural Points Representation for Graph-based Semantic Monocular Localization and Mapping. CoRR abs/2206.10263 (2022) - [i9]Puze Liu, Kuo Zhang, Davide Tateo, Snehal Jauhri, Zhiyuan Hu, Jan Peters, Georgia Chalvatzaki:
Safe reinforcement learning of dynamic high-dimensional robotic tasks: navigation, manipulation, interaction. CoRR abs/2209.13308 (2022) - 2021
- [j1]Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters:
MushroomRL: Simplifying Reinforcement Learning Research. J. Mach. Learn. Res. 22: 131:1-131:5 (2021) - [c10]Puze Liu, Davide Tateo, Haitham Bou-Ammar, Jan Peters:
Robot Reinforcement Learning on the Constraint Manifold. CoRL 2021: 1357-1366 - [c9]João Carvalho, Davide Tateo, Fabio Muratore, Jan Peters:
An Empirical Analysis of Measure-Valued Derivatives for Policy Gradients. IJCNN 2021: 1-10 - [c8]Puze Liu, Davide Tateo, Haitham Bou-Ammar, Jan Peters:
Efficient and Reactive Planning for High Speed Robot Air Hockey. IROS 2021: 586-593 - [i8]Puze Liu, Davide Tateo, Haitham Bou-Ammar, Jan Peters:
Efficient and Reactive Planning for High Speed Robot Air Hockey. CoRR abs/2107.06140 (2021) - [i7]João Carvalho, Davide Tateo, Fabio Muratore, Jan Peters:
An Empirical Analysis of Measure-Valued Derivatives for Policy Gradients. CoRR abs/2107.09359 (2021) - [i6]Julen Urain, Davide Tateo, Jan Peters:
Learning Stable Vector Fields on Lie Groups. CoRR abs/2110.11774 (2021) - 2020
- [c7]Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters:
Sharing Knowledge in Multi-Task Deep Reinforcement Learning. ICLR 2020 - [c6]Julen Urain, Michele Ginesi, Davide Tateo, Jan Peters:
ImitationFlow: Learning Deep Stable Stochastic Dynamic Systems by Normalizing Flows. IROS 2020: 5231-5237 - [i5]Simone Parisi, Davide Tateo, Maximilian Hensel, Carlo D'Eramo, Jan Peters, Joni Pajarinen:
Long-Term Visitation Value for Deep Exploration in Sparse Reward Reinforcement Learning. CoRR abs/2001.00119 (2020) - [i4]Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters:
MushroomRL: Simplifying Reinforcement Learning Research. CoRR abs/2001.01102 (2020) - [i3]Riad Akrour, Davide Tateo, Jan Peters:
Reinforcement Learning from a Mixture of Interpretable Experts. CoRR abs/2006.05911 (2020) - [i2]Julen Urain, Michele Ginesi, Davide Tateo, Jan Peters:
ImitationFlow: Learning Deep Stable Stochastic Dynamic Systems by Normalizing Flows. CoRR abs/2010.13129 (2020) - [i1]Julen Urain, Davide Tateo, Tianyu Ren, Jan Peters:
Structured Policy Representation: Imposing Stability in arbitrarily conditioned dynamic systems. CoRR abs/2012.06224 (2020)
2010 – 2019
- 2019
- [b1]Davide Tateo:
Building structured hierarchical agents. Polytechnic University of Milan, Italy, 2019 - [c5]Carolina Beretta, Cecilia Brizzolari, Davide Tateo, Alessandro Riva, Francesco Amigoni:
A Sampling-Based Algorithm for Planning Smooth Nonholonomic Paths. ECMR 2019: 1-7 - [c4]Davide Tateo, Idil Su Erdenlig, Andrea Bonarini:
Graph-Based Design of Hierarchical Reinforcement Learning Agents. IROS 2019: 1003-1009 - 2018
- [c3]Davide Tateo, Jacopo Banfi, Alessandro Riva, Francesco Amigoni, Andrea Bonarini:
Multiagent Connected Path Planning: PSPACE-Completeness and How to Deal With It. AAAI 2018: 4735-4742 - 2017
- [c2]Davide Tateo, Carlo D'Eramo, Alessandro Nuara, Marcello Restelli, Andrea Bonarini:
Exploiting structure and uncertainty of Bellman updates in Markov decision processes. SSCI 2017: 1-8 - [c1]Davide Tateo, Matteo Pirotta, Marcello Restelli, Andrea Bonarini:
Gradient-based minimization for multi-expert Inverse Reinforcement Learning. SSCI 2017: 1-8
Coauthor Index
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