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Jan Peters 0001
Jan R. Peters
Person information
- affiliation: TU Darmstadt, Department of Computer Science, Germany
- affiliation: Max Planck Institute for Intelligent Systems, Tübingen, Germany
- affiliation: Max Planck Institute for Biological Cybernetics, Tübingen, Germany
- affiliation: University of Southern California Los Angeles, Computational Learning and Motion Control Lab, CA, USA
Other persons with the same name
- Jan Peters 0002 — Flemish Institute for Technological Research, Department of Environmental Quality (and 1 more)
- Jan Peters 0003 — Fraunhofer Institute for Computer Graphics Research (IGD)
- Jan Peters 0004 — University of Hannover, Institute of Assembly Technology, Garbsen, Germany
- Jan Peters 0005 — University of Cologne, Department of Psychology, Germany
- Jan Peters 0006 — Powerledger, Perth, WA, Australia (and 1 more)
- Jan Peters 0007 — University Medical-Center Hamburg-Eppendorf, Germany
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2020 – today
- 2024
- [j155]Yang Weng, Sehwa Chun, Masaki Ohashi, Takumi Matsuda, Yuki Sekimori, Joni Pajarinen, Jan Peters, Toshihiro Maki:
Autonomous underwater vehicle link alignment control in unknown environments using reinforcement learning. J. Field Robotics 41(6): 1724-1743 (2024) - [j154]Hany Abdulsamad, Peter Nickl, Pascal Klink, Jan Peters:
Variational Hierarchical Mixtures for Probabilistic Learning of Inverse Dynamics. IEEE Trans. Pattern Anal. Mach. Intell. 46(4): 1950-1963 (2024) - [j153]Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen:
On the Benefit of Optimal Transport for Curriculum Reinforcement Learning. IEEE Trans. Pattern Anal. Mach. Intell. 46(11): 7191-7204 (2024) - [j152]Vignesh Prasad, Alap Kshirsagar, Dorothea Koert, Ruth Stock-Homburg, Jan Peters, Georgia Chalvatzaki:
MoVEInt: Mixture of Variational Experts for Learning Human-Robot Interactions From Demonstrations. IEEE Robotics Autom. Lett. 9(7): 6043-6050 (2024) - [j151]Michael Drolet, Simon Stepputtis, Siva Kailas, Ajinkya Jain, Jan Peters, Stefan Schaal, Heni Ben Amor:
A Comparison of Imitation Learning Algorithms for Bimanual Manipulation. IEEE Robotics Autom. Lett. 9(10): 8579-8586 (2024) - [j150]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) - [j149]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) - [j148]Niklas Funk, Erik Helmut, Georgia Chalvatzaki, Roberto Calandra, Jan Peters:
Evetac: An Event-Based Optical Tactile Sensor for Robotic Manipulation. IEEE Trans. Robotics 40: 3812-3832 (2024) - [c292]Cedric Derstroff, Mattia Cerrato, Jannis Brugger, Jan Peters, Stefan Kramer:
Peer Learning: Learning Complex Policies in Groups from Scratch via Action Recommendations. AAAI 2024: 11766-11774 - [c291]Théo Vincent, Alberto Maria Metelli, Boris Belousov, Jan Peters, Marcello Restelli, Carlo D'Eramo:
Parameterized Projected Bellman Operator. AAAI 2024: 15402-15410 - [c290]Philipp Holzmann, Maik Pfefferkorn, Jan Peters, Rolf Findeisen:
Learning Energy-Efficient Trajectory Planning for Robotic Manipulators Using Bayesian Optimization. ECC 2024: 1374-1379 - [c289]Yasemin Göksu, Antonio De Almeida Correia, Vignesh Prasad, Alap Kshirsagar, Dorothea Koert, Jan Peters, Georgia Chalvatzaki:
Kinematically Constrained Human-like Bimanual Robot-to-Human Handovers. HRI (Companion) 2024: 497-501 - [c288]Fabian Hahne, Vignesh Prasad, Alap Kshirsagar, Dorothea Koert, Ruth Maria Stock-Homburg, Jan Peters, Georgia Chalvatzaki:
Transition State Clustering for Interaction Segmentation and Learning. HRI (Companion) 2024: 512-516 - [c287]Aditya Bhatt, Daniel Palenicek, Boris Belousov, Max Argus, Artemij Amiranashvili, Thomas Brox, Jan Peters:
CrossQ: Batch Normalization in Deep Reinforcement Learning for Greater Sample Efficiency and Simplicity. ICLR 2024 - [c286]Firas Al-Hafez, Guoping Zhao, Jan Peters, Davide Tateo:
Time-Efficient Reinforcement Learning with Stochastic Stateful Policies. ICLR 2024 - [c285]Ahmed Hendawy, Jan Peters, Carlo D'Eramo:
Multi-Task Reinforcement Learning with Mixture of Orthogonal Experts. ICLR 2024 - [c284]Aryaman Reddi, Maximilian Tölle, Jan Peters, Georgia Chalvatzaki, Carlo D'Eramo:
Robust Adversarial Reinforcement Learning via Bounded Rationality Curricula. ICLR 2024 - [c283]Gabriele Tiboni, Pascal Klink, Jan Peters, Tatiana Tommasi, Carlo D'Eramo, Georgia Chalvatzaki:
Domain Randomization via Entropy Maximization. ICLR 2024 - [c282]Duy Minh Ho Nguyen, Nina Lukashina, Tai Nguyen, An T. Le, TrungTin Nguyen, Nhat Ho, Jan Peters, Daniel Sonntag, Viktor Zaverkin, Mathias Niepert:
Structure-Aware E(3)-Invariant Molecular Conformer Aggregation Networks. ICML 2024 - [c281]Abby O'Neill, Abdul Rehman, Abhiram Maddukuri, Abhishek Gupta, Abhishek Padalkar, Abraham Lee, Acorn Pooley, Agrim Gupta, Ajay Mandlekar, Ajinkya Jain, Albert Tung, Alex Bewley, Alexander Herzog, Alex Irpan, Alexander Khazatsky, Anant Rai, Anchit Gupta, Andrew Wang, Anikait Singh, Animesh Garg, Aniruddha Kembhavi, Annie Xie, Anthony Brohan, Antonin Raffin, Archit Sharma, Arefeh Yavary, Arhan Jain, Ashwin Balakrishna, Ayzaan Wahid, Ben Burgess-Limerick, Beomjoon Kim, Bernhard Schölkopf, Blake Wulfe, Brian Ichter, Cewu Lu, Charles Xu, Charlotte Le, Chelsea Finn, Chen Wang, Chenfeng Xu, Cheng Chi, Chenguang Huang, Christine Chan, Christopher Agia, Chuer Pan, Chuyuan Fu, Coline Devin, Danfei Xu, Daniel Morton, Danny Driess, Daphne Chen, Deepak Pathak, Dhruv Shah, Dieter Büchler, Dinesh Jayaraman, Dmitry Kalashnikov, Dorsa Sadigh, Edward Johns, Ethan Paul Foster, Fangchen Liu, Federico Ceola, Fei Xia, Feiyu Zhao, Freek Stulp, Gaoyue Zhou, Gaurav S. Sukhatme, Gautam Salhotra, Ge Yan, Gilbert Feng, Giulio Schiavi, Glen Berseth, Gregory Kahn, Guanzhi Wang, Hao Su, Haoshu Fang, Haochen Shi, Henghui Bao, Heni Ben Amor, Henrik I. Christensen, Hiroki Furuta, Homer Walke, Hongjie Fang, Huy Ha, Igor Mordatch, Ilija Radosavovic, Isabel Leal, Jacky Liang, Jad Abou-Chakra, Jaehyung Kim, Jaimyn Drake, Jan Peters, Jan Schneider, Jasmine Hsu, Jeannette Bohg, Jeffrey Bingham, Jeffrey Wu, Jensen Gao, Jiaheng Hu, Jiajun Wu, Jialin Wu, Jiankai Sun, Jianlan Luo, Jiayuan Gu, Jie Tan, Jihoon Oh, Jimmy Wu, Jingpei Lu, Jingyun Yang, Jitendra Malik, João Silvério, Joey Hejna, Jonathan Booher, Jonathan Tompson, Jonathan Yang, Jordi Salvador, Joseph J. Lim, Junhyek Han, Kaiyuan Wang, Kanishka Rao, Karl Pertsch, Karol Hausman, Keegan Go, Keerthana Gopalakrishnan, Ken Goldberg, Kendra Byrne, Kenneth Oslund, Kento Kawaharazuka, Kevin Black, Kevin Lin, Kevin Zhang, Kiana Ehsani, Kiran Lekkala, Kirsty Ellis, Krishan Rana, Krishnan Srinivasan, Kuan Fang, Kunal Pratap Singh, Kuo-Hao Zeng, Kyle Hatch, Kyle Hsu, Laurent Itti, Lawrence Yunliang Chen, Lerrel Pinto, Li Fei-Fei, Liam Tan, Linxi Jim Fan, Lionel Ott, Lisa Lee, Luca Weihs, Magnum Chen, Marion Lepert, Marius Memmel, Masayoshi Tomizuka, Masha Itkina, Mateo Guaman Castro, Max Spero, Maximilian Du, Michael Ahn, Michael C. Yip, Mingtong Zhang, Mingyu Ding, Minho Heo, Mohan Kumar Srirama, Mohit Sharma, Moo Jin Kim, Naoaki Kanazawa, Nicklas Hansen, Nicolas Heess, Nikhil J. Joshi, Niko Sünderhauf, Ning Liu, Norman Di Palo, Nur Muhammad (Mahi) Shafiullah, Oier Mees, Oliver Kroemer, Osbert Bastani, Pannag R. Sanketi, Patrick Tree Miller, Patrick Yin, Paul Wohlhart, Peng Xu, Peter David Fagan, Peter Mitrano, Pierre Sermanet, Pieter Abbeel, Priya Sundaresan, Qiuyu Chen, Quan Vuong, Rafael Rafailov, Ran Tian, Ria Doshi, Roberto Martín-Martín, Rohan Baijal, Rosario Scalise, Rose Hendrix, Roy Lin, Runjia Qian, Ruohan Zhang, Russell Mendonca, Rutav Shah, Ryan Hoque, Ryan Julian, Samuel Bustamante, Sean Kirmani, Sergey Levine, Shan Lin, Sherry Moore, Shikhar Bahl, Shivin Dass, Shubham D. Sonawani, Shuran Song, Sichun Xu, Siddhant Haldar, Siddharth Karamcheti, Simeon Adebola, Simon Guist, Soroush Nasiriany, Stefan Schaal, Stefan Welker, Stephen Tian, Subramanian Ramamoorthy, Sudeep Dasari, Suneel Belkhale, Sungjae Park, Suraj Nair, Suvir Mirchandani, Takayuki Osa, Tanmay Gupta, Tatsuya Harada, Tatsuya Matsushima, Ted Xiao, Thomas Kollar, Tianhe Yu, Tianli Ding, Todor Davchev, Tony Z. Zhao, Travis Armstrong, Trevor Darrell, Trinity Chung, Vidhi Jain, Vincent Vanhoucke, Wei Zhan, Wenxuan Zhou, Wolfram Burgard, Xi Chen, Xiaolong Wang, Xinghao Zhu, Xinyang Geng, Xiyuan Liu, Liangwei Xu, Xuanlin Li, Yao Lu, Yecheng Jason Ma, Yejin Kim, Yevgen Chebotar, Yifan Zhou, Yifeng Zhu, Yilin Wu, Ying Xu, Yixuan Wang, Yonatan Bisk, Yoonyoung Cho, Youngwoon Lee, Yuchen Cui, Yue Cao, Yueh-Hua Wu, Yujin Tang, Yuke Zhu, Yunchu Zhang, Yunfan Jiang, Yunshuang Li, Yunzhu Li, Yusuke Iwasawa, Yutaka Matsuo, Zehan Ma, Zhuo Xu, Zichen Jeff Cui, Zichen Zhang, Zipeng Lin:
Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration. ICRA 2024: 6892-6903 - [c280]Alina Böhm, Tim Schneider, Boris Belousov, Alap Kshirsagar, Lisa Pui Yee Lin, Katja Doerschner, Knut Drewing, Constantin A. Rothkopf, Jan Peters:
What Matters for Active Texture Recognition With Vision-Based Tactile Sensors. ICRA 2024: 15099-15105 - [c279]Felix Wiebe, Niccolò Turcato, Alberto Dalla Libera, Chi Zhang, Théo Vincent, Shubham Vyas, Giulio Giacomuzzo, Ruggero Carli, Diego Romeres, Akhil Sathuluri, Markus Zimmermann, Boris Belousov, Jan Peters, Frank Kirchner, Shivesh Kumar:
Reinforcement Learning for Athletic Intelligence: Lessons from the 1st "AI Olympics with RealAIGym" Competition. IJCAI 2024: 8833-8837 - [i207]Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters:
Sharing Knowledge in Multi-Task Deep Reinforcement Learning. CoRR abs/2401.09561 (2024) - [i206]Duy M. H. Nguyen, Nina Lukashina, Tai Nguyen, An T. Le, TrungTin Nguyen, Nhat Ho, Jan Peters, Daniel Sonntag, Viktor Zaverkin, Mathias Niepert:
Structure-Aware E(3)-Invariant Molecular Conformer Aggregation Networks. CoRR abs/2402.01975 (2024) - [i205]Yasemin Göksu, Antonio De Almeida Correia, Vignesh Prasad, Alap Kshirsagar, Dorothea Koert, Jan Peters, Georgia Chalvatzaki:
Kinematically Constrained Human-like Bimanual Robot-to-Human Handovers. CoRR abs/2402.14525 (2024) - [i204]Fabian Hahne, Vignesh Prasad, Alap Kshirsagar, Dorothea Koert, Ruth Maria Stock-Homburg, Jan Peters, Georgia Chalvatzaki:
Transition State Clustering for Interaction Segmentation and Learning. CoRR abs/2402.14548 (2024) - [i203]Alessandro G. Bottero, Carlos E. Luis, Julia Vinogradska, Felix Berkenkamp, Jan Peters:
Information-Theoretic Safe Bayesian Optimization. CoRR abs/2402.15347 (2024) - [i202]Théo Vincent, Daniel Palenicek, Boris Belousov, Jan Peters, Carlo D'Eramo:
Iterated Q-Network: Beyond the One-Step Bellman Operator. CoRR abs/2403.02107 (2024) - [i201]Alina Böhm, Tim Schneider, Boris Belousov, Alap Kshirsagar, Lisa Pui Yee Lin, Katja Doerschner, Knut Drewing, Constantin A. Rothkopf, Jan Peters:
What Matters for Active Texture Recognition With Vision-Based Tactile Sensors. CoRR abs/2403.13701 (2024) - [i200]Puze Liu, Haitham Bou-Ammar, Jan Peters, Davide Tateo:
Safe Reinforcement Learning on the Constraint Manifold: Theory and Applications. CoRR abs/2404.09080 (2024) - [i199]Christoph Zelch, Jan Peters, Oskar von Stryk:
Clustering of Motion Trajectories by a Distance Measure Based on Semantic Features. CoRR abs/2404.17269 (2024) - [i198]Noah Becker, Erik Gattung, Kay Hansel, Tim Schneider, Yaonan Zhu, Yasuhisa Hasegawa, Jan Peters:
Integrating Visuo-tactile Sensing with Haptic Feedback for Teleoperated Robot Manipulation. CoRR abs/2404.19585 (2024) - [i197]Daniel Palenicek, Theo Gruner, Tim Schneider, Alina Böhm, Janis Lenz, Inga Pfenning, Eric Krämer, Jan Peters:
Learning Tactile Insertion in the Real World. CoRR abs/2405.00383 (2024) - [i196]Théo Vincent, Fabian Wahren, Jan Peters, Boris Belousov, Carlo D'Eramo:
Adaptive Q-Network: On-the-fly Target Selection for Deep Reinforcement Learning. CoRR abs/2405.16195 (2024) - [i195]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) - [i194]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) - [i193]Duy M. H. Nguyen, An T. Le, Trung Q. Nguyen, Nghiem T. Diep, Tai Nguyen, Duy Duong-Tran, Jan Peters, Li Shen, Mathias Niepert, Daniel Sonntag:
Dude: Dual Distribution-Aware Context Prompt Learning For Large Vision-Language Model. CoRR abs/2407.04489 (2024) - [i192]Vignesh Prasad, Alap Kshirsagar, Dorothea Koert, Ruth Stock-Homburg, Jan Peters, Georgia Chalvatzaki:
MoVEInt: Mixture of Variational Experts for Learning Human-Robot Interactions from Demonstrations. CoRR abs/2407.07636 (2024) - [i191]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) - [i190]Cheng Qian, Julen Urain, Kevin Zakka, Jan Peters:
PianoMime: Learning a Generalist, Dexterous Piano Player from Internet Demonstrations. CoRR abs/2407.18178 (2024) - [i189]Moritz Meser, Aditya Bhatt, Boris Belousov, Jan Peters:
MuJoCo MPC for Humanoid Control: Evaluation on HumanoidBench. CoRR abs/2408.00342 (2024) - [i188]Julen Urain, Ajay Mandlekar, Yilun Du, Mahi Shafiullah, Danfei Xu, Katerina Fragkiadaki, Georgia Chalvatzaki, Jan Peters:
Deep Generative Models in Robotics: A Survey on Learning from Multimodal Demonstrations. CoRR abs/2408.04380 (2024) - [i187]Michael Drolet, Simon Stepputtis, Siva Kailas, Ajinkya Jain, Jan Peters, Stefan Schaal, Heni Ben Amor:
A Comparison of Imitation Learning Algorithms for Bimanual Manipulation. CoRR abs/2408.06536 (2024) - [i186]Joe Watson, Chen Song, Oliver Weeger, Theo Gruner, An T. Le, Kay Hansel, Ahmed Hendawy, Oleg Arenz, Will Trojak, Miles Cranmer, Carlo D'Eramo, Fabian Bülow, Tanmay Goyal, Jan Peters, Martin W. Hoffman:
Machine Learning with Physics Knowledge for Prediction: A Survey. CoRR abs/2408.09840 (2024) - [i185]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) - [i184]Dominik Straub, Tobias F. Niehues, Jan Peters, Constantin A. Rothkopf:
Inverse decision-making using neural amortized Bayesian actors. CoRR abs/2409.03710 (2024) - [i183]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) - [i182]Niklas Funk, Julen Urain, Joao Carvalho, Vignesh Prasad, Georgia Chalvatzaki, Jan Peters:
ActionFlow: Equivariant, Accurate, and Efficient Policies with Spatially Symmetric Flow Matching. CoRR abs/2409.04576 (2024) - [i181]Junning Huang, Davide Tateo, Puze Liu, Jan Peters:
Adaptive Control based Friction Estimation for Tracking Control of Robot Manipulators. CoRR abs/2409.05054 (2024) - [i180]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) - [i179]Jonas Guenster, Puze Liu, Jan Peters, Davide Tateo:
Handling Long-Term Safety and Uncertainty in Safe Reinforcement Learning. CoRR abs/2409.12045 (2024) - [i178]Carlos E. Luis, Alessandro G. Bottero, Julia Vinogradska, Felix Berkenkamp, Jan Peters:
Uncertainty Representations in State-Space Layers for Deep Reinforcement Learning under Partial Observability. CoRR abs/2409.16824 (2024) - 2023
- [j147]Shangding Gu, Alap Kshirsagar, Yali Du, Guang Chen, Jan Peters, Alois Knoll:
A human-centered safe robot reinforcement learning framework with interactive behaviors. Frontiers Neurorobotics 17 (2023) - [j146]Michael Lutter, Jan Peters:
Combining physics and deep learning to learn continuous-time dynamics models. Int. J. Robotics Res. 42(3): 83-107 (2023) - [j145]Julen Urain, Anqi Li, Puze Liu, Carlo D'Eramo, Jan Peters:
Composable energy policies for reactive motion generation and reinforcement learning. Int. J. Robotics Res. 42(10): 827-858 (2023) - [j144]Andreas Look, Melih Kandemir, Barbara Rakitsch, Jan Peters:
A Deterministic Approximation to Neural SDEs. IEEE Trans. Pattern Anal. Mach. Intell. 45(4): 4023-4037 (2023) - [j143]Michael Lutter, Boris Belousov, Shie Mannor, Dieter Fox, Animesh Garg, Jan Peters:
Continuous-Time Fitted Value Iteration for Robust Policies. IEEE Trans. Pattern Anal. Mach. Intell. 45(5): 5534-5548 (2023) - [j142]Hamish Flynn, David Reeb, Melih Kandemir, Jan Peters:
PAC-Bayes Bounds for Bandit Problems: A Survey and Experimental Comparison. IEEE Trans. Pattern Anal. Mach. Intell. 45(12): 15308-15327 (2023) - [j141]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) - [j140]Siwei Ju, Peter van Vliet, Oleg Arenz, Jan Peters:
Digital Twin of a Driver-in-the-Loop Race Car Simulation With Contextual Reinforcement Learning. IEEE Robotics Autom. Lett. 8(7): 4107-4114 (2023) - [j139]Dieter Büchler, Roberto Calandra, Jan Peters:
Learning to Control Highly Accelerated Ballistic Movements on Muscular Robots. Robotics Auton. Syst. 159: 104230 (2023) - [j138]Andreas Look, Barbara Rakitsch, Melih Kandemir, Jan Peters:
Cheap and Deterministic Inference for Deep State-Space Models of Interacting Dynamical Systems. Trans. Mach. Learn. Res. 2023 (2023) - [j137]Stefan Löckel, Siwei Ju, Maximilian Schaller, Peter van Vliet, Jan Peters:
An Adaptive Human Driver Model for Realistic Race Car Simulations. IEEE Trans. Syst. Man Cybern. Syst. 53(11): 6718-6730 (2023) - [c278]Carlos E. Luis, Alessandro G. Bottero, Julia Vinogradska, Felix Berkenkamp, Jan Peters:
Model-Based Uncertainty in Value Functions. AISTATS 2023: 8029-8052 - [c277]Yaonan Zhu, Shukrullo Nazirjonov, Bingheng Jiang, Jacinto Colan, Tadayoshi Aoyama, Yasuhisa Hasegawa, Boris Belousov, Kay Hansel, Jan Peters:
Visual Tactile Sensor Based Force Estimation for Position-Force Teleoperation. CBS 2023: 49-52 - [c276]David Rother, Thomas H. Weisswange, Jan Peters:
Disentangling Interaction Using Maximum Entropy Reinforcement Learning in Multi-Agent Systems. ECAI 2023: 1994-2001 - [c275]Christoph Zelch, Jan Peters, Oskar von Stryk:
Clustering of Motion Trajectories by a Distance Measure Based on Semantic Features. Humanoids 2023: 1-8 - [c274]Firas Al-Hafez, Davide Tateo, Oleg Arenz, Guoping Zhao, Jan Peters:
LS-IQ: Implicit Reward Regularization for Inverse Reinforcement Learning. ICLR 2023 - [c273]Daniel Palenicek, Michael Lutter, Joao Carvalho, Jan Peters:
Diminishing Return of Value Expansion Methods in Model-Based Reinforcement Learning. ICLR 2023 - [c272]Christoph Zelch, Jan Peters, Oskar von Stryk:
Start State Selection for Control Policy Learning from Optimal Trajectories. ICRA 2023: 3247-3253 - [c271]Julen Urain, Niklas Funk, Jan Peters, Georgia Chalvatzaki:
SE(3)-DiffusionFields: Learning smooth cost functions for joint grasp and motion optimization through diffusion. ICRA 2023: 5923-5930 - [c270]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 - [c269]Kay Hansel, Julen Urain, Jan Peters, Georgia Chalvatzaki:
Hierarchical Policy Blending as Inference for Reactive Robot Control. ICRA 2023: 10181-10188 - [c268]João Carvalho, An T. Le, Mark Baierl, Dorothea Koert, Jan Peters:
Motion Planning Diffusion: Learning and Planning of Robot Motions with Diffusion Models. IROS 2023: 1916-1923 - [c267]Luca Lach, Niklas Funk, Robert Haschke, Séverin Lemaignan, Helge Joachim Ritter, Jan Peters, Georgia Chalvatzaki:
Placing by Touching: An Empirical Study on the Importance of Tactile Sensing for Precise Object Placing. IROS 2023: 8964-8971 - [c266]An T. Le, Kay Hansel, Jan Peters, Georgia Chalvatzaki:
Hierarchical Policy Blending As Optimal Transport. L4DC 2023: 797-812 - [c265]An T. Le, Georgia Chalvatzaki, Armin Biess, Jan Peters:
Accelerating Motion Planning via Optimal Transport. NeurIPS 2023 - [c264]Hamish Flynn, David Reeb, Melih Kandemir, Jan R. Peters:
Improved Algorithms for Stochastic Linear Bandits Using Tail Bounds for Martingale Mixtures. NeurIPS 2023 - [c263]Theo Gruner, Boris Belousov, Fabio Muratore, Daniel Palenicek, Jan R. Peters:
Pseudo-Likelihood Inference. NeurIPS 2023 - [i177]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) - [i176]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) - [i175]Carlos E. Luis, Alessandro G. Bottero, Julia Vinogradska, Felix Berkenkamp, Jan Peters:
Model-Based Uncertainty in Value Functions. CoRR abs/2302.12526 (2023) - [i174]Shangding Gu, Alap Kshirsagar, Yali Du, Guang Chen, Yaodong Yang, Jan Peters, Alois C. Knoll:
A Human-Centered Safe Robot Reinforcement Learning Framework with Interactive Behaviors. CoRR abs/2302.13137 (2023) - [i173]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) - [i172]Daniel Palenicek, Michael Lutter, Joao Carvalho, Jan Peters:
Diminishing Return of Value Expansion Methods in Model-Based Reinforcement Learning. CoRR abs/2303.03955 (2023) - [i171]Johanna Bethge, Maik Pfefferkorn, Alexander Rose, Jan Peters, Rolf Findeisen:
Model Predictive Control with Gaussian-Process-Supported Dynamical Constraints for Autonomous Vehicles. CoRR abs/2303.04725 (2023) - [i170]Andreas Look, Melih Kandemir, Barbara Rakitsch, Jan Peters:
Cheap and Deterministic Inference for Deep State-Space Models of Interacting Dynamical Systems. CoRR abs/2305.01773 (2023) - [i169]Jihao Andreas Lin, Joe Watson, Pascal Klink, Jan Peters:
Function-Space Regularization for Deep Bayesian Classification. CoRR abs/2307.06055 (2023) - [i168]João Carvalho, An T. Le, Mark Baierl, Dorothea Koert, Jan Peters:
Motion Planning Diffusion: Learning and Planning of Robot Motions with Diffusion Models. CoRR abs/2308.01557 (2023) - [i167]Carlos E. Luis, Alessandro G. Bottero, Julia Vinogradska, Felix Berkenkamp, Jan Peters:
Value-Distributional Model-Based Reinforcement Learning. CoRR abs/2308.06590 (2023) - [i166]Andreas Look, Melih Kandemir, Barbara Rakitsch, Jan Peters:
Sampling-Free Probabilistic Deep State-Space Models. CoRR abs/2309.08256 (2023) - [i165]Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen:
On the Benefit of Optimal Transport for Curriculum Reinforcement Learning. CoRR abs/2309.14091 (2023) - [i164]Pascal Klink, Florian Wolf, Kai Ploeger, Jan Peters, Joni Pajarinen:
Tracking Control for a Spherical Pendulum via Curriculum Reinforcement Learning. CoRR abs/2309.14096 (2023) - [i163]Hamish Flynn, David Reeb, Melih Kandemir, Jan Peters:
Improved Algorithms for Stochastic Linear Bandits Using Tail Bounds for Martingale Mixtures. CoRR abs/2309.14298 (2023) - [i162]An T. Le, Georgia Chalvatzaki, Armin Biess, Jan Peters:
Accelerating Motion Planning via Optimal Transport. CoRR abs/2309.15970 (2023) - [i161]Aryaman Reddi, Maximilian Tölle, Jan Peters, Georgia Chalvatzaki, Carlo D'Eramo:
Robust Adversarial Reinforcement Learning via Bounded Rationality Curricula. CoRR abs/2311.01642 (2023) - [i160]Gabriele Tiboni, Pascal Klink, Jan Peters, Tatiana Tommasi, Carlo D'Eramo, Georgia Chalvatzaki:
Domain Randomization via Entropy Maximization. CoRR abs/2311.01885 (2023) - [i159]Firas Al-Hafez, Guoping Zhao, Jan Peters, Davide Tateo:
LocoMuJoCo: A Comprehensive Imitation Learning Benchmark for Locomotion. CoRR abs/2311.02496 (2023) - [i158]Firas Al-Hafez, Guoping Zhao, Jan Peters, Davide Tateo:
Time-Efficient Reinforcement Learning with Stochastic Stateful Policies. CoRR abs/2311.04082 (2023) - [i157]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) - [i156]Ahmed Hendawy, Jan Peters, Carlo D'Eramo:
Multi-Task Reinforcement Learning with Mixture of Orthogonal Experts. CoRR abs/2311.11385 (2023) - [i155]Vignesh Prasad, Lea Heitlinger, Dorothea Koert, Ruth Stock-Homburg, Jan Peters, Georgia Chalvatzaki:
Learning Multimodal Latent Dynamics for Human-Robot Interaction. CoRR abs/2311.16380 (2023) - [i154]Theo Gruner, Boris Belousov, Fabio Muratore, Daniel Palenicek, Jan Peters:
Pseudo-Likelihood Inference. CoRR