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ORCIDGerhard Neumann
Person information
- affiliation: Karlsruhe Institute of Technology, Institute for Anthropomatics and Robotics, Germany
- affiliation: University of Lincoln, Center for Autonomous Systems (L-CAS), UK
- affiliation (former): TU Darmstadt, Department of Computer Science, Germany
- affiliation (PhD 2012): Graz University of Technology, Austria
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2020 – today
- 2024
[j48]Paul Maria Scheikl
, Nicolas Schreiber, Christoph Haas, Niklas Freymuth, Gerhard Neumann, Rudolf Lioutikov, Franziska Mathis-Ullrich:
Movement Primitive Diffusion: Learning Gentle Robotic Manipulation of Deformable Objects. IEEE Robotics Autom. Lett. 9(6): 5338-5345 (2024)- [c117]Xinkai Jiang, Paul Mattes, Xiaogang Jia, Nicolas Schreiber, Gerhard Neumann, Rudolf Lioutikov:
A Comprehensive User Study on Augmented Reality-Based Data Collection Interfaces for Robot Learning. HRI 2024: 333-342 - [c116]Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Nadia Figueroa, Gerhard Neumann, Leonel Rozo:
Neural Contractive Dynamical Systems. ICLR 2024 - [c115]Xiaogang Jia, Denis Blessing, Xinkai Jiang, Moritz Reuss, Atalay Donat, Rudolf Lioutikov, Gerhard Neumann:
Towards Diverse Behaviors: A Benchmark for Imitation Learning with Human Demonstrations. ICLR 2024 - [c114]Ge Li, Hongyi Zhou, Dominik Roth, Serge Thilges, Fabian Otto, Rudolf Lioutikov, Gerhard Neumann:
Open the Black Box: Step-based Policy Updates for Temporally-Correlated Episodic Reinforcement Learning. ICLR 2024 - [c113]Denis Blessing, Xiaogang Jia, Johannes Esslinger, Francisco Vargas, Gerhard Neumann:
Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling. ICML 2024 - [c112]Onur Celik, Aleksandar Taranovic, Gerhard Neumann:
Acquiring Diverse Skills using Curriculum Reinforcement Learning with Mixture of Experts. ICML 2024 - [c111]Rebekka Charlotte Peter, Steffen Peikert, Ludwig Haide, Doan Xuan Viet Pham, Tahar Chettaoui, Eleonora Tagliabue, Paul Maria Scheikl, Johannes Fauser, Matthias Hillenbrand, Gerhard Neumann, Franziska Mathis-Ullrich:
Lens Capsule Tearing in Cataract Surgery using Reinforcement Learning. ICRA 2024: 15501-15508 - [c110]Pit Henrich, Balázs Gyenes, Paul Maria Scheikl, Gerhard Neumann, Franziska Mathis-Ullrich:
Registered and Segmented Deformable Object Reconstruction from a Single View Point Cloud. WACV 2024: 3117-3126 - [i75]Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Nadia Figueroa, Gerhard Neumann, Leonel Rozo:
Neural Contractive Dynamical Systems. CoRR abs/2401.09352 (2024) - [i74]Ge Li, Hongyi Zhou, Dominik Roth, Serge Thilges, Fabian Otto, Rudolf Lioutikov, Gerhard Neumann:
Open the Black Box: Step-based Policy Updates for Temporally-Correlated Episodic Reinforcement Learning. CoRR abs/2401.11437 (2024) - [i73]Tobias Würth, Niklas Freymuth, Clemens Zimmerling, Gerhard Neumann, Luise Kärger:
Physics-informed MeshGraphNets (PI-MGNs): Neural finite element solvers for non-stationary and nonlinear simulations on arbitrary meshes. CoRR abs/2402.10681 (2024) - [i72]Xiaogang Jia, Denis Blessing, Xinkai Jiang, Moritz Reuss, Atalay Donat, Rudolf Lioutikov, Gerhard Neumann:
Towards Diverse Behaviors: A Benchmark for Imitation Learning with Human Demonstrations. CoRR abs/2402.14606 (2024) - [i71]Fabian Otto, Philipp Becker, Ngo Anh Vien, Gerhard Neumann:
Vlearn: Off-Policy Learning with Efficient State-Value Function Estimation. CoRR abs/2403.04453 (2024) - [i70]Onur Celik, Aleksandar Taranovic, Gerhard Neumann:
Acquiring Diverse Skills using Curriculum Reinforcement Learning with Mixture of Experts. CoRR abs/2403.06966 (2024) - [i69]Denis Blessing, Xiaogang Jia, Johannes Esslinger, Francisco Vargas, Gerhard Neumann:
Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling. CoRR abs/2406.07423 (2024) - [i68]Xiaogang Jia, Qian Wang, Atalay Donat, Bowen Xing, Ge Li, Hongyi Zhou, Onur Celik, Denis Blessing, Rudolf Lioutikov, Gerhard Neumann:
MaIL: Improving Imitation Learning with Mamba. CoRR abs/2406.08234 (2024) - [i67]Niklas Freymuth, Philipp Dahlinger, Tobias Würth, Simon Reisch, Luise Kärger, Gerhard Neumann:
Adaptive Swarm Mesh Refinement using Deep Reinforcement Learning with Local Rewards. CoRR abs/2406.08440 (2024) - [i66]Hongyi Zhou, Denis Blessing, Ge Li, Onur Celik, Xiaogang Jia, Gerhard Neumann, Rudolf Lioutikov:
Variational Distillation of Diffusion Policies into Mixture of Experts. CoRR abs/2406.12538 (2024) - [i65]Niklas Freymuth, Philipp Dahlinger, Tobias Würth, Philipp Becker, Aleksandar Taranovic, Onno Grönheim, Luise Kärger, Gerhard Neumann:
Iterative Sizing Field Prediction for Adaptive Mesh Generation From Expert Demonstrations. CoRR abs/2406.14161 (2024) - [i64]Philipp Becker, Niklas Freymuth, Gerhard Neumann:
KalMamba: Towards Efficient Probabilistic State Space Models for RL under Uncertainty. CoRR abs/2406.15131 (2024) - [i63]Claudius Kienle, Benjamin Alt, Onur Celik, Philipp Becker, Darko Katic, Rainer Jäkel, Gerhard Neumann:
MuTT: A Multimodal Trajectory Transformer for Robot Skills. CoRR abs/2407.15660 (2024) - 2023
- [j47]Jairo Inga, Miriam Ruess, Jan Heinrich Robens, Thomas Nelius, Simon Rothfuß, Sean Kille, Philipp Dahlinger, Andreas Lindenmann, Roland Thomaschke, Gerhard Neumann, Sven Matthiesen, Sören Hohmann, Andrea Kiesel:
Human-machine symbiosis: A multivariate perspective for physically coupled human-machine systems. Int. J. Hum. Comput. Stud. 170: 102926 (2023) - [j46]Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Gerhard Neumann, Leonel Rozo:
Reactive motion generation on learned Riemannian manifolds. Int. J. Robotics Res. 42(10): 729-754 (2023) - [j45]Paul Maria Scheikl, Balázs Gyenes, Rayan Younis, Christoph Haas, Gerhard Neumann, Martin Wagner, Franziska Mathis-Ullrich:
LapGym - An Open Source Framework for Reinforcement Learning in Robot-Assisted Laparoscopic Surgery. J. Mach. Learn. Res. 24: 368:1-368:42 (2023) - [j44]Ge Li, Zeqi Jin, Michael Volpp, Fabian Otto, Rudolf Lioutikov, Gerhard Neumann:
ProDMP: A Unified Perspective on Dynamic and Probabilistic Movement Primitives. IEEE Robotics Autom. Lett. 8(4): 2325-2332 (2023) - [j43]Fabian Duffhauss, Sebastian Koch, Hanna Ziesche, Ngo Anh Vien, Gerhard Neumann:
SyMFM6D: Symmetry-Aware Multi-Directional Fusion for Multi-View 6D Object Pose Estimation. IEEE Robotics Autom. Lett. 8(9): 5315-5322 (2023) - [j42]Oleg Arenz, Philipp Dahlinger, Zihan Ye, Michael Volpp, Gerhard Neumann:
A Unified Perspective on Natural Gradient Variational Inference with Gaussian Mixture Models. Trans. Mach. Learn. Res. 2023 (2023) - [c109]Ning Gao, Bernard Hohmann, Gerhard Neumann:
Enhancing Interpretable Object Abstraction via Clustering-based Slot Initialization. BMVC 2023: 471-477 - [c108]Ning Gao, Ngo Anh Vien, Hanna Ziesche, Gerhard Neumann:
SA6D: Self-Adaptive Few-Shot 6D Pose Estimator for Novel and Occluded Objects. CoRL 2023: 1572-1595 - [c107]Jonas Linkerhägner, Niklas Freymuth, Paul Maria Scheikl, Franziska Mathis-Ullrich, Gerhard Neumann:
Grounding Graph Network Simulators using Physical Sensor Observations. ICLR 2023 - [c106]Aleksandar Taranovic, Andras Gabor Kupcsik, Niklas Freymuth, Gerhard Neumann:
Adversarial Imitation Learning with Preferences. ICLR 2023 - [c105]Michael Volpp, Philipp Dahlinger, Philipp Becker, Christian Daniel, Gerhard Neumann:
Accurate Bayesian Meta-Learning by Accurate Task Posterior Inference. ICLR 2023 - [c104]Maximilian Xiling Li, Onur Celik, Philipp Becker, Denis Blessing, Rudolf Lioutikov, Gerhard Neumann:
Curriculum-Based Imitation of Versatile Skills. ICRA 2023: 2951-2957 - [c103]Denis Blessing, Onur Celik, Xiaogang Jia, Moritz Reuss, Maximilian Li, Rudolf Lioutikov, Gerhard Neumann:
Information Maximizing Curriculum: A Curriculum-Based Approach for Learning Versatile Skills. NeurIPS 2023 - [c102]Niklas Freymuth, Philipp Dahlinger, Tobias Würth, Simon Reisch, Luise Kärger, Gerhard Neumann:
Swarm Reinforcement Learning for Adaptive Mesh Refinement. NeurIPS 2023 - [c101]Florian Seligmann, Philipp Becker, Michael Volpp, Gerhard Neumann:
Beyond Deep Ensembles: A Large-Scale Evaluation of Bayesian Deep Learning under Distribution Shift. NeurIPS 2023 - [c100]Vaisakh Shaj, Saleh Gholam Zadeh, Ozan Demir, Luiz R. Douat, Gerhard Neumann:
Multi Time Scale World Models. NeurIPS 2023 - [i62]Philipp Becker, Sebastian Markgraf, Fabian Otto, Gerhard Neumann:
Reinforcement Learning from Multiple Sensors via Joint Representations. CoRR abs/2302.05342 (2023) - [i61]Paul Maria Scheikl, Balázs Gyenes, Rayan Younis, Christoph Haas, Gerhard Neumann, Martin Wagner, Franziska Mathis-Ullrich:
LapGym - An Open Source Framework for Reinforcement Learning in Robot-Assisted Laparoscopic Surgery. CoRR abs/2302.09606 (2023) - [i60]Jonas Linkerhägner, Niklas Freymuth, Paul Maria Scheikl, Franziska Mathis-Ullrich, Gerhard Neumann:
Grounding Graph Network Simulators using Physical Sensor Observations. CoRR abs/2302.11864 (2023) - [i59]Denis Blessing, Onur Celik, Xiaogang Jia, Moritz Reuss, Maximilian Xiling Li, Rudolf Lioutikov, Gerhard Neumann:
Information Maximizing Curriculum: A Curriculum-Based Approach for Training Mixtures of Experts. CoRR abs/2303.15349 (2023) - [i58]Niklas Freymuth, Philipp Dahlinger, Tobias Würth, Luise Kärger, Gerhard Neumann:
Swarm Reinforcement Learning For Adaptive Mesh Refinement. CoRR abs/2304.00818 (2023) - [i57]Maximilian Xiling Li, Onur Celik, Philipp Becker, Denis Blessing, Rudolf Lioutikov, Gerhard Neumann:
Curriculum-Based Imitation of Versatile Skills. CoRR abs/2304.05171 (2023) - [i56]Florian Seligmann, Philipp Becker, Michael Volpp, Gerhard Neumann:
Beyond Deep Ensembles: A Large-Scale Evaluation of Bayesian Deep Learning under Distribution Shift. CoRR abs/2306.12306 (2023) - [i55]Fabian Otto, Hongyi Zhou, Onur Celik, Ge Li, Rudolf Lioutikov, Gerhard Neumann:
MP3: Movement Primitive-Based (Re-)Planning Policy. CoRR abs/2306.12729 (2023) - [i54]Fabian Duffhauss, Sebastian Koch, Hanna Ziesche, Ngo Anh Vien, Gerhard Neumann:
SyMFM6D: Symmetry-aware Multi-directional Fusion for Multi-View 6D Object Pose Estimation. CoRR abs/2307.00306 (2023) - [i53]Philipp Blättner, Johannes Brand, Gerhard Neumann, Ngo Anh Vien:
DMFC-GraspNet: Differentiable Multi-Fingered Robotic Grasp Generation in Cluttered Scenes. CoRR abs/2308.00456 (2023) - [i52]Ning Gao, Bernard Hohmann, Gerhard Neumann:
Enhancing Interpretable Object Abstraction via Clustering-based Slot Initialization. CoRR abs/2308.11369 (2023) - [i51]Ning Gao, Ngo Anh Vien, Hanna Ziesche, Gerhard Neumann:
SA6D: Self-Adaptive Few-Shot 6D Pose Estimator for Novel and Occluded Objects. CoRR abs/2308.16528 (2023) - [i50]Vaisakh Shaj, Saleh Gholam Zadeh, Ozan Demir, Luiz Ricardo Douat, Gerhard Neumann:
Multi Time Scale World Models. CoRR abs/2310.18534 (2023) - [i49]Philipp Dahlinger, Philipp Becker, Maximilian Hüttenrauch, Gerhard Neumann:
Information-Theoretic Trust Regions for Stochastic Gradient-Based Optimization. CoRR abs/2310.20574 (2023) - [i48]Philipp Dahlinger, Niklas Freymuth, Michael Volpp, Tai Hoang, Gerhard Neumann:
Latent Task-Specific Graph Network Simulators. CoRR abs/2311.05256 (2023) - [i47]Pit Henrich, Balázs Gyenes, Paul Maria Scheikl, Gerhard Neumann, Franziska Mathis-Ullrich:
Registered and Segmented Deformable Object Reconstruction from a Single View Point Cloud. CoRR abs/2311.07357 (2023) - [i46]Paul Maria Scheikl, Nicolas Schreiber, Christoph Haas, Niklas Freymuth, Gerhard Neumann, Rudolf Lioutikov, Franziska Mathis-Ullrich:
Movement Primitive Diffusion: Learning Gentle Robotic Manipulation of Deformable Objects. CoRR abs/2312.10008 (2023) - [i45]Benjamin Alt, Urs Keßner, Aleksandar Taranovic, Darko Katic, Andreas Hermann, Rainer Jäkel, Gerhard Neumann:
Domain-Specific Fine-Tuning of Large Language Models for Interactive Robot Programming. CoRR abs/2312.13905 (2023) - 2022
- [j41]Philipp Becker, Gerhard Neumann:
On Uncertainty in Deep State Space Models for Model-Based Reinforcement Learning. Trans. Mach. Learn. Res. 2022 (2022) - [c99]Fabian Otto, Onur Celik, Hongyi Zhou, Hanna Ziesche, Ngo Anh Vien, Gerhard Neumann:
Deep Black-Box Reinforcement Learning with Movement Primitives. CoRL 2022: 1244-1265 - [c98]Niklas Freymuth, Nicolas Schreiber, Aleksandar Taranovic, Philipp Becker, Gerhard Neumann:
Inferring Versatile Behavior from Demonstrations by Matching Geometric Descriptors. CoRL 2022: 1379-1389 - [c97]Ning Gao, Hanna Ziesche, Ngo Anh Vien, Michael Volpp, Gerhard Neumann:
What Matters For Meta-Learning Vision Regression Tasks? CVPR 2022: 14756-14766 - [c96]Fabian Duffhauss, Ngo Anh Vien, Hanna Ziesche, Gerhard Neumann:
FusionVAE: A Deep Hierarchical Variational Autoencoder for RGB Image Fusion. ECCV (39) 2022: 674-691 - [c95]Vaisakh Shaj, Dieter Büchler, Rohit Sonker, Philipp Becker, Gerhard Neumann:
Hidden Parameter Recurrent State Space Models For Changing Dynamics Scenarios. ICLR 2022 - [c94]Baris Serhan, Harit Pandya, Ayse Küçükyilmaz, Gerhard Neumann:
Push-to-See: Learning Non-Prehensile Manipulation to Enhance Instance Segmentation via Deep Q-Learning. ICRA 2022: 1513-1519 - [c93]Oussama Zenkri, Ngo Anh Vien, Gerhard Neumann:
Hierarchical Policy Learning for Mechanical Search. ICRA 2022: 1954-1960 - [c92]Fabian Duffhauss, Tobias Demmler, Gerhard Neumann:
MV6D: Multi-View 6D Pose Estimation on RGB-D Frames Using a Deep Point-wise Voting Network. IROS 2022: 3568-3575 - [c91]Abdalkarim Mohtasib, Gerhard Neumann, Heriberto Cuayáhuitl:
Robot Policy Learning from Demonstration Using Advantage Weighting and Early Termination. IROS 2022: 7414-7420 - [c90]Moritz Reuss, Niels van Duijkeren, Robert Krug, Philipp Becker, Vaisakh Shaj, Gerhard Neumann:
End-to-End Learning of Hybrid Inverse Dynamics Models for Precise and Compliant Impedance Control. Robotics: Science and Systems 2022 - [i44]Oussama Zenkri, Ngo Anh Vien, Gerhard Neumann:
Hierarchical Policy Learning for Mechanical Search. CoRR abs/2202.13680 (2022) - [i43]Ning Gao, Hanna Ziesche, Ngo Anh Vien, Michael Volpp, Gerhard Neumann:
What Matters For Meta-Learning Vision Regression Tasks? CoRR abs/2203.04905 (2022) - [i42]Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Gerhard Neumann, Leonel Dario Rozo:
Reactive Motion Generation on Learned Riemannian Manifolds. CoRR abs/2203.07761 (2022) - [i41]Ruijie Chen, Ning Gao, Ngo Anh Vien, Hanna Ziesche, Gerhard Neumann:
Meta-Learning Regrasping Strategies for Physical-Agnostic Objects. CoRR abs/2205.11110 (2022) - [i40]Moritz Reuss, Niels van Duijkeren, Robert Krug, Philipp Becker, Vaisakh Shaj, Gerhard Neumann:
End-to-End Learning of Hybrid Inverse Dynamics Models for Precise and Compliant Impedance Control. CoRR abs/2205.13804 (2022) - [i39]Maximilian Hüttenrauch, Gerhard Neumann:
Regret-Aware Black-Box Optimization with Natural Gradients, Trust-Regions and Entropy Control. CoRR abs/2206.06090 (2022) - [i38]Yumeng Li, Ning Gao, Hanna Ziesche, Gerhard Neumann:
Category-Agnostic 6D Pose Estimation with Conditional Neural Processes. CoRR abs/2206.07162 (2022) - [i37]Vaisakh Shaj, Dieter Buchler, Rohit Sonker, Philipp Becker, Gerhard Neumann:
Hidden Parameter Recurrent State Space Models For Changing Dynamics Scenarios. CoRR abs/2206.14697 (2022) - [i36]Abdalkarim Mohtasib, Gerhard Neumann, Heriberto Cuayáhuitl:
Robot Policy Learning from Demonstration Using Advantage Weighting and Early Termination. CoRR abs/2208.00478 (2022) - [i35]Fabian Duffhauss, Tobias Demmler, Gerhard Neumann:
MV6D: Multi-View 6D Pose Estimation on RGB-D Frames Using a Deep Point-wise Voting Network. CoRR abs/2208.01172 (2022) - [i34]Fabian Duffhauss, Ngo Anh Vien, Hanna Ziesche, Gerhard Neumann:
FusionVAE: A Deep Hierarchical Variational Autoencoder for RGB Image Fusion. CoRR abs/2209.11277 (2022) - [i33]Oleg Arenz, Philipp Dahlinger, Zihan Ye, Michael Volpp, Gerhard Neumann:
A Unified Perspective on Natural Gradient Variational Inference with Gaussian Mixture Models. CoRR abs/2209.11533 (2022) - [i32]Ge Li, Zeqi Jin, Michael Volpp, Fabian Otto, Rudolf Lioutikov, Gerhard Neumann:
ProDMPs: A Unified Perspective on Dynamic and Probabilistic Movement Primitives. CoRR abs/2210.01531 (2022) - [i31]Niklas Freymuth, Nicolas Schreiber, Philipp Becker, Aleksandar Taranovic, Gerhard Neumann:
Inferring Versatile Behavior from Demonstrations by Matching Geometric Descriptors. CoRR abs/2210.08121 (2022) - [i30]Philipp Becker, Gerhard Neumann:
On Uncertainty in Deep State Space Models for Model-Based Reinforcement Learning. CoRR abs/2210.09256 (2022) - [i29]Fabian Otto, Onur Celik, Hongyi Zhou, Hanna Ziesche, Ngo Anh Vien, Gerhard Neumann:
Deep Black-Box Reinforcement Learning with Movement Primitives. CoRR abs/2210.09622 (2022) - 2021
- [j40]R. B. Ashith Shyam, Zhou Hao, Umberto Montanaro, Shilp Dixit, Arunkumar Rathinam, Yang Gao, Gerhard Neumann, Saber Fallah:
Autonomous Robots for Space: Trajectory Learning and Adaptation Using Imitation. Frontiers Robotics AI 8: 638849 (2021) - [j39]Riccardo Polvara, Francesco Del Duchetto, Gerhard Neumann, Marc Hanheide:
Navigate-and-Seek: A Robotics Framework for People Localization in Agricultural Environments. IEEE Robotics Autom. Lett. 6(4): 6577-6584 (2021) - [j38]Juan Parras, Maximilian Hüttenrauch, Santiago Zazo, Gerhard Neumann:
Deep Reinforcement Learning for Attacking Wireless Sensor Networks. Sensors 21(12): 4060 (2021) - [c89]Onur Celik, Dongzhuoran Zhou, Ge Li, Philipp Becker, Gerhard Neumann:
Specializing Versatile Skill Libraries using Local Mixture of Experts. CoRL 2021: 1423-1433 - [c88]Maximilian Hüttenrauch, Gerhard Neumann:
Coordinate ascent MORE with adaptive entropy control for population-based regret minimization. GECCO Companion 2021: 1493-1497 - [c87]Fabian Otto, Philipp Becker, Ngo Anh Vien, Hanna Carolin Maria Ziesche, Gerhard Neumann:
Differentiable Trust Region Layers for Deep Reinforcement Learning. ICLR 2021 - [c86]Michael Volpp, Fabian Flürenbrock, Lukas Großberger, Christian Daniel, Gerhard Neumann:
Bayesian Context Aggregation for Neural Processes. ICLR 2021 - [c85]Paul Maria Scheikl, Balázs Gyenes, Tornike Davitashvili, Rayan Younis, André Schulze, Beat P. Müller-Stich, Gerhard Neumann, Martin Wagner, Franziska Mathis-Ullrich:
Cooperative Assistance in Robotic Surgery through Multi-Agent Reinforcement Learning. IROS 2021: 1859-1864 - [c84]Alireza Ranjbar, Ngo Anh Vien, Hanna Ziesche, Joschka Boedecker, Gerhard Neumann:
Residual Feedback Learning for Contact-Rich Manipulation Tasks with Uncertainty. IROS 2021: 2383-2390 - [c83]Kim Tien Ly, Mithun Poozhiyil, Harit Pandya, Gerhard Neumann, Ayse Küçükyilmaz:
Intent-Aware Predictive Haptic Guidance and its Application to Shared Control Teleoperation. RO-MAN 2021: 565-572 - [c82]Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Gerhard Neumann, Leonel Dario Rozo:
Learning Riemannian Manifolds for Geodesic Motion Skills. Robotics: Science and Systems 2021 - [c81]Abdalkarim Mohtasib, Gerhard Neumann, Heriberto Cuayáhuitl:
A Study on Dense and Sparse (Visual) Rewards in Robot Policy Learning. TAROS 2021: 3-13 - [e1]Aleksandra Faust, David Hsu, Gerhard Neumann:
Conference on Robot Learning, 8-11 November 2021, London, UK. Proceedings of Machine Learning Research 164, PMLR 2021 [contents] - [i28]Fabian Otto, Philipp Becker, Ngo Anh Vien, Hanna Carolin Ziesche, Gerhard Neumann:
Differentiable Trust Region Layers for Deep Reinforcement Learning. CoRR abs/2101.09207 (2021) - [i27]Alireza Ranjbar, Ngo Anh Vien, Hanna Ziesche, Joschka Boedecker, Gerhard Neumann:
Residual Feedback Learning for Contact-Rich Manipulation Tasks with Uncertainty. CoRR abs/2106.04306 (2021) - [i26]Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Gerhard Neumann, Leonel Dario Rozo:
Learning Riemannian Manifolds for Geodesic Motion Skills. CoRR abs/2106.04315 (2021) - [i25]Ngo Anh Vien, Gerhard Neumann:
Differentiable Robust LQR Layers. CoRR abs/2106.05535 (2021) - [i24]Riccardo Polvara, Francesco Del Duchetto, Gerhard Neumann, Marc Hanheide:
Navigate-and-Seek: a Robotics Framework for People Localization in Agricultural Environments. CoRR abs/2107.03850 (2021) - [i23]Abdalkarim Mohtasib, Gerhard Neumann, Heriberto Cuayáhuitl:
A Study on Dense and Sparse (Visual) Rewards in Robot Policy Learning. CoRR abs/2108.03222 (2021) - [i22]Paul Maria Scheikl, Balázs Gyenes, Tornike Davitashvili, Rayan Younis, André Schulze, Beat P. Müller-Stich, Gerhard Neumann, Martin Wagner, Franziska Mathis-Ullrich:
Cooperative Assistance in Robotic Surgery through Multi-Agent Reinforcement Learning. CoRR abs/2110.04857 (2021) - [i21]Niklas Freymuth, Philipp Becker, Gerhard Neumann:
Versatile Inverse Reinforcement Learning via Cumulative Rewards. CoRR abs/2111.07667 (2021) - [i20]Giao Nguyen-Quynh, Philipp Becker, Chen Qiu, Maja Rudolph, Gerhard Neumann:
Switching Recurrent Kalman Networks. CoRR abs/2111.08291 (2021) - [i19]Jairo Inga, Miriam Ruess, Jan Heinrich Robens, Thomas Nelius, Sean Kille, Philipp Dahlinger, Roland Thomaschke, Gerhard Neumann, Sven Matthiesen, Sören Hohmann, Andrea Kiesel:
Human-machine Symbiosis: A Multivariate Perspective for Physically Coupled Human-machine Systems. CoRR abs/2111.14681 (2021) - [i18]Onur Celik, Dongzhuoran Zhou, Ge Li, Philipp Becker, Gerhard Neumann:
Specializing Versatile Skill Libraries using Local Mixture of Experts. CoRR abs/2112.04216 (2021) - 2020
- [j37]Oleg Arenz, Mingjun Zhong, Gerhard Neumann:
Trust-Region Variational Inference with Gaussian Mixture Models. J. Mach. Learn. Res. 21: 163:1-163:60 (2020) - [j36]Riccardo Polvara, Manuel Fernández-Carmona, Gerhard Neumann, Marc Hanheide:
Next-Best-Sense: A Multi-Criteria Robotic Exploration Strategy for RFID Tags Discovery. IEEE Robotics Autom. Lett. 5(3): 4477-4484 (2020) - [j35]Joni Pajarinen, Oleg Arenz, Jan Peters, Gerhard Neumann:
Probabilistic Approach to Physical Object Disentangling. IEEE Robotics Autom. Lett. 5(4): 5510-5517 (2020) - [j34]Riccardo Polvara, Massimiliano Patacchiola, Marc Hanheide, Gerhard Neumann:
Sim-to-Real Quadrotor Landing via Sequential Deep Q-Networks and Domain Randomization. Robotics 9(1): 8 (2020) - [j33]Jayant Singh, Aravinda Ramakrishnan Srinivasan, Gerhard Neumann, Ayse Küçükyilmaz:
Haptic-Guided Teleoperation of a 7-DoF Collaborative Robot Arm With an Identical Twin Master. IEEE Trans. Haptics 13(1): 246-252 (2020) - [j32]Firas Abi-Farraj, Claudio Pacchierotti, Oleg Arenz, Gerhard Neumann, Paolo Robuffo Giordano:
A Haptic Shared-Control Architecture for Guided Multi-Target Robotic Grasping. IEEE Trans. Haptics 13(2): 270-285 (2020) - [j31]Sebastián Gómez-González, Gerhard Neumann, Bernhard Schölkopf, Jan Peters:
Adaptation and Robust Learning of Probabilistic Movement Primitives. IEEE Trans. Robotics 36(2): 366-379 (2020) - [c80]Soran Parsa, Disha Kamale, Sariah Mghames, Kiyanoush Nazari, Tommaso Pardi, Aravinda Ramakrishnan Srinivasan, Gerhard Neumann, Marc Hanheide, Amir Ghalamzan E:
Haptic-guided shared control grasping: collision-free manipulation. CASE 2020: 1552-1557 - [c79]Vaisakh Shaj, Philipp Becker, Dieter Büchler, Harit Pandya, Niels van Duijkeren, C. James Taylor, Marc Hanheide, Gerhard Neumann:
Action-Conditional Recurrent Kalman Networks For Forward and Inverse Dynamics Learning. CoRL 2020: 765-781 - [c78]Philipp Becker, Oleg Arenz, Gerhard Neumann:
Expected Information Maximization: Using the I-Projection for Mixture Density Estimation. ICLR 2020 - [c77]