Davide Tateo - RankMe

65 papers A* 6A 6B 1Misc 4Journal 41Unranked 6

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Adaptive Control Based Friction Estimation for Tracking Control of Robot Manipulators. IEEE Robotics Autom. Lett. Junning Huang, Davide Tateo, Puze Liu, Jan Peters
2025	—	`conf`	Robust Localization, Mapping, and Navigation for Quadruped Robots. ECMR Dyuman Aditya, Junning Huang, Nico Bohlinger, Piotr Kicki, Krzysztof Walas, Jan Peters, Matteo Luperto, Davide Tateo
2025	J	`jnl`	Robust Localization, Mapping, and Navigation for Quadruped Robots. CoRR Dyuman Aditya, Junning Huang, Nico Bohlinger, Piotr Kicki, Krzysztof Walas, Jan Peters, Matteo Luperto, Davide Tateo
2025	J	`jnl`	Safe Reinforcement Learning on the Constraint Manifold: Theory and Applications. IEEE Trans. Robotics Puze Liu, Haitham Bou-Ammar, Jan Peters, Davide Tateo
2025	J	`jnl`	Towards Safe Robot Foundation Models Using Inductive Biases. CoRR Maximilian Tölle, Theo Gruner, Daniel Palenicek, Tim Schneider, Jonas Günster, Joe Watson, Davide Tateo, Puze Liu, Jan Peters
2025	J	`jnl`	Towards Safe Robot Foundation Models. CoRR Maximilian Tölle, Theo Gruner, Daniel Palenicek, Jonas Günster, Puze Liu, Joe Watson, Davide Tateo, Jan Peters
2024	—	`conf`	A Holistic Concept on AI Assistance for Robot-Supported Reconnaissance and Mitigation of Acute Radiation Hazard Situations. SSRR Kevin Daun, Frederik Bark, Davide Tateo, Jan Peters, Johannes Heinlein, Janine Wendt, Nils Heidemann, Ivana Kruijff-Korbayová, Stefan Kohlbrecher, Jens Friedrich, Désirée Martin, Michael W. Schmidt, Rafaela Hillerbrand, Oskar von Stryk
2024	A*	`conf`	A Retrospective on the Robot Air Hockey Challenge: Benchmarking Robust, Reliable, and Safe Learning Techniques for Real-world Robotics. NeurIPS Puze Liu, Jonas Günster, Niklas Funk, Simon Gröger, Dong Chen, Haitham Bou-Ammar, Julius Jankowski, Ante Maric, Sylvain Calinon, Andrej Orsula, Miguel S. Olivares-Méndez, Hongyi Zhou, Rudolf Lioutikov, Gerhard Neumann, Amarildo Likmeta, Amirhossein Zhalehmehrabi, Thomas Bonenfant, Marcello Restelli, Davide Tateo, Ziyuan Liu, Jan R. Peters
2024	J	`jnl`	A Retrospective on the Robot Air Hockey Challenge: Benchmarking Robust, Reliable, and Safe Learning Techniques for Real-world Robotics. CoRR Puze Liu, Jonas Guenster, Niklas Funk, Simon Gröger, Dong Chen, Haitham Bou-Ammar, Julius Jankowski, Ante Maric, Sylvain Calinon, Andrej Orsula, Miguel S. Olivares-Méndez, Hongyi Zhou, Rudolf Lioutikov, Gerhard Neumann, Amarildo Likmeta, Amirhossein Zhalehmehrabi, Thomas Bonenfant, Marcello Restelli, Davide Tateo, Ziyuan Liu, Jan Peters
2024	J	`jnl`	Adaptive Control based Friction Estimation for Tracking Control of Robot Manipulators. CoRR Junning Huang, Davide Tateo, Puze Liu, Jan Peters
2024	Misc	`conf`	Bridging the gap between Learning-to-plan, Motion Primitives and Safe Reinforcement Learning. CoRL Piotr Kicki, Davide Tateo, Puze Liu, Jonas Günster, Jan Peters, Krzysztof Walas
2024	J	`jnl`	Bridging the gap between Learning-to-plan, Motion Primitives and Safe Reinforcement Learning. CoRR Piotr Kicki, Davide Tateo, Puze Liu, Jonas Guenster, Jan Peters, Krzysztof Walas
2024	J	`jnl`	Energy-based Contact Planning under Uncertainty for Robot Air Hockey. CoRR Julius Jankowski, Ante Maric, Puze Liu, Davide Tateo, Jan Peters, Sylvain Calinon
2024	—	`conf`	Exciting Action: Investigating Efficient Exploration for Learning Musculoskeletal Humanoid Locomotion. Humanoids Henri-Jacques Geiß, Firas Al-Hafez, André Seyfarth, Jan Peters, Davide Tateo
2024	J	`jnl`	Exciting Action: Investigating Efficient Exploration for Learning Musculoskeletal Humanoid Locomotion. CoRR Henri-Jacques Geiß, Firas Al-Hafez, André Seyfarth, Jan Peters, Davide Tateo
2024	J	`jnl`	Fast Kinodynamic Planning on the Constraint Manifold With Deep Neural Networks. IEEE Trans. Robotics Piotr Kicki, Puze Liu, Davide Tateo, Haitham Bou-Ammar, Krzysztof Walas, Piotr Skrzypczynski, Jan Peters
2024	Misc	`conf`	Handling Long-Term Safety and Uncertainty in Safe Reinforcement Learning. CoRL Jonas Günster, Puze Liu, Jan Peters, Davide Tateo
2024	J	`jnl`	Handling Long-Term Safety and Uncertainty in Safe Reinforcement Learning. CoRR Jonas Guenster, Puze Liu, Jan Peters, Davide Tateo
2024	Misc	`conf`	One Policy to Run Them All: an End-to-end Learning Approach to Multi-Embodiment Locomotion. CoRL Nico Bohlinger, Grzegorz Czechmanowski, Maciej Piotr Krupka, Piotr Kicki, Krzysztof Walas, Jan Peters, Davide Tateo
2024	J	`jnl`	One Policy to Run Them All: an End-to-end Learning Approach to Multi-Embodiment Locomotion. CoRR Nico Bohlinger, Grzegorz Czechmanowski, Maciej Krupka, Piotr Kicki, Krzysztof Walas, Jan Peters, Davide Tateo
2024	J	`jnl`	ROS-LLM: A ROS framework for embodied AI with task feedback and structured reasoning. CoRR 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
2024	J	`jnl`	Safe Reinforcement Learning on the Constraint Manifold: Theory and Applications. CoRR Puze Liu, Haitham Bou-Ammar, Jan Peters, Davide Tateo
2024	J	`jnl`	Safe and Efficient Path Planning Under Uncertainty via Deep Collision Probability Fields. IEEE Robotics Autom. Lett. Felix Herrmann, Sebastian Zach, Jacopo Banfi, Jan Peters, Georgia Chalvatzaki, Davide Tateo
2024	J	`jnl`	Safe and Efficient Path Planning under Uncertainty via Deep Collision Probability Fields. CoRR Felix Herrmann, Sebastian Zach, Jacopo Banfi, Jan Peters, Georgia Chalvatzaki, Davide Tateo
2024	J	`jnl`	Sharing Knowledge in Multi-Task Deep Reinforcement Learning. CoRR Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters
2024	A*	`conf`	Time-Efficient Reinforcement Learning with Stochastic Stateful Policies. ICLR Firas Al-Hafez, Guoping Zhao, Jan Peters, Davide Tateo
2024	A	`conf`	Zero-Shot Transfer of a Tactile-based Continuous Force Control Policy from Simulation to Robot. IROS Luca Lach, Robert Haschke, Davide Tateo, Jan Peters, Helge J. Ritter, Júlia Borràs Sol, Carme Torras
2023	J	`jnl`	Fast Kinodynamic Planning on the Constraint Manifold with Deep Neural Networks. CoRR Piotr Kicki, Puze Liu, Davide Tateo, Haitham Bou-Ammar, Krzysztof Walas, Piotr Skrzypczynski, Jan Peters
2023	A*	`conf`	LS-IQ: Implicit Reward Regularization for Inverse Reinforcement Learning. ICLR Firas Al-Hafez, Davide Tateo, Oleg Arenz, Guoping Zhao, Jan Peters
2023	J	`jnl`	LS-IQ: Implicit Reward Regularization for Inverse Reinforcement Learning. CoRR Firas Al-Hafez, Davide Tateo, Oleg Arenz, Guoping Zhao, Jan Peters
2023	J	`jnl`	Learning-Based Design and Control for Quadrupedal Robots With Parallel-Elastic Actuators. IEEE Robotics Autom. Lett. Filip Bjelonic, Joonho Lee, Philip Arm, Dhionis V. Sako, Davide Tateo, Jan Peters, Marco Hutter
2023	J	`jnl`	Learning-based Design and Control for Quadrupedal Robots with Parallel-Elastic Actuators. CoRR Filip Bjelonic, Joonho Lee, Philip Arm, Dhionis V. Sako, Davide Tateo, Jan Peters, Marco Hutter
2023	J	`jnl`	LocoMuJoCo: A Comprehensive Imitation Learning Benchmark for Locomotion. CoRR Firas Al-Hafez, Guoping Zhao, Jan Peters, Davide Tateo
2023	A*	`conf`	Safe Reinforcement Learning of Dynamic High-Dimensional Robotic Tasks: Navigation, Manipulation, Interaction. ICRA Puze Liu, Kuo Zhang, Davide Tateo, Snehal Jauhri, Zhiyuan Hu, Jan Peters, Georgia Chalvatzaki
2023	J	`jnl`	Time-Efficient Reinforcement Learning with Stochastic Stateful Policies. CoRR Firas Al-Hafez, Guoping Zhao, Jan Peters, Davide Tateo
2023	J	`jnl`	Towards Transferring Tactile-based Continuous Force Control Policies from Simulation to Robot. CoRR Luca Lach, Robert Haschke, Davide Tateo, Jan Peters, Helge J. Ritter, Júlia Borràs Sol, Carme Torras
2022	J	`jnl`	Continuous Action Reinforcement Learning From a Mixture of Interpretable Experts. IEEE Trans. Pattern Anal. Mach. Intell. Riad Akrour, Davide Tateo, Jan Peters
2022	A	`conf`	Dimensionality Reduction and Prioritized Exploration for Policy Search. AISTATS Marius Memmel, Puze Liu, Davide Tateo, Jan Peters
2022	J	`jnl`	Dimensionality Reduction and Prioritized Exploration for Policy Search. CoRR Marius Memmel, Puze Liu, Davide Tateo, Jan Peters
2022	J	`jnl`	Learning Stable Vector Fields on Lie Groups. IEEE Robotics Autom. Lett. Julen Urain, Davide Tateo, Jan Peters
2022	J	`jnl`	Long-Term Visitation Value for Deep Exploration in Sparse-Reward Reinforcement Learning. Algorithms Simone Parisi, Davide Tateo, Maximilian Hensel, Carlo D'Eramo, Jan Peters, Joni Pajarinen
2022	J	`jnl`	Object Structural Points Representation for Graph-based Semantic Monocular Localization and Mapping. CoRR Davide Tateo, Davide Antonio Cucci, Matteo Matteucci, Andrea Bonarini
2022	A	`conf`	Regularized Deep Signed Distance Fields for Reactive Motion Generation. IROS Puze Liu, Kuo Zhang, Davide Tateo, Snehal Jauhri, Jan Peters, Georgia Chalvatzaki
2022	J	`jnl`	Regularized Deep Signed Distance Fields for Reactive Motion Generation. CoRR Puze Liu, Kuo Zhang, Davide Tateo, Snehal Jauhri, Jan Peters, Georgia Chalvatzaki
2022	J	`jnl`	Safe reinforcement learning of dynamic high-dimensional robotic tasks: navigation, manipulation, interaction. CoRR Puze Liu, Kuo Zhang, Davide Tateo, Snehal Jauhri, Zhiyuan Hu, Jan Peters, Georgia Chalvatzaki
2021	B	`conf`	An Empirical Analysis of Measure-Valued Derivatives for Policy Gradients. IJCNN João Carvalho, Davide Tateo, Fabio Muratore, Jan Peters
2021	J	`jnl`	An Empirical Analysis of Measure-Valued Derivatives for Policy Gradients. CoRR João Carvalho, Davide Tateo, Fabio Muratore, Jan Peters
2021	A	`conf`	Efficient and Reactive Planning for High Speed Robot Air Hockey. IROS Puze Liu, Davide Tateo, Haitham Bou-Ammar, Jan Peters
2021	J	`jnl`	Efficient and Reactive Planning for High Speed Robot Air Hockey. CoRR Puze Liu, Davide Tateo, Haitham Bou-Ammar, Jan Peters
2021	J	`jnl`	Learning Stable Vector Fields on Lie Groups. CoRR Julen Urain, Davide Tateo, Jan Peters
2021	J	`jnl`	MushroomRL: Simplifying Reinforcement Learning Research. J. Mach. Learn. Res. Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters
2021	Misc	`conf`	Robot Reinforcement Learning on the Constraint Manifold. CoRL Puze Liu, Davide Tateo, Haitham Bou-Ammar, Jan Peters
2020	A	`conf`	ImitationFlow: Learning Deep Stable Stochastic Dynamic Systems by Normalizing Flows. IROS Julen Urain, Michele Ginesi, Davide Tateo, Jan Peters
2020	J	`jnl`	ImitationFlow: Learning Deep Stable Stochastic Dynamic Systems by Normalizing Flows. CoRR Julen Urain, Michele Ginesi, Davide Tateo, Jan Peters
2020	J	`jnl`	Long-Term Visitation Value for Deep Exploration in Sparse Reward Reinforcement Learning. CoRR Simone Parisi, Davide Tateo, Maximilian Hensel, Carlo D'Eramo, Jan Peters, Joni Pajarinen
2020	J	`jnl`	MushroomRL: Simplifying Reinforcement Learning Research. CoRR Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters
2020	J	`jnl`	Reinforcement Learning from a Mixture of Interpretable Experts. CoRR Riad Akrour, Davide Tateo, Jan Peters
2020	A*	`conf`	Sharing Knowledge in Multi-Task Deep Reinforcement Learning. ICLR Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters
2020	J	`jnl`	Structured Policy Representation: Imposing Stability in arbitrarily conditioned dynamic systems. CoRR Julen Urain, Davide Tateo, Tianyu Ren, Jan Peters
2019	—	`conf`	A Sampling-Based Algorithm for Planning Smooth Nonholonomic Paths. ECMR Carolina Beretta, Cecilia Brizzolari, Davide Tateo, Alessandro Riva, Francesco Amigoni
2019	—	`—`	Building structured hierarchical agents. Davide Tateo
2019	A	`conf`	Graph-Based Design of Hierarchical Reinforcement Learning Agents. IROS Davide Tateo, Idil Su Erdenlig, Andrea Bonarini
2018	A*	`conf`	Multiagent Connected Path Planning: PSPACE-Completeness and How to Deal With It. AAAI Davide Tateo, Jacopo Banfi, Alessandro Riva, Francesco Amigoni, Andrea Bonarini
2017	—	`conf`	Exploiting structure and uncertainty of Bellman updates in Markov decision processes. SSCI Davide Tateo, Carlo D'Eramo, Alessandro Nuara, Marcello Restelli, Andrea Bonarini
2017	—	`conf`	Gradient-based minimization for multi-expert Inverse Reinforcement Learning. SSCI Davide Tateo, Matteo Pirotta, Marcello Restelli, Andrea Bonarini