Rudolf Lioutikov

发表

Learning Manipulation by Sequencing Motor Primitives with a Two-Armed Robot

Oliver Kroemer, Jan Peters, Guilherme Maeda, 2014, IAS.

A Probabilistic Framework for Semi-autonomous Robots Based on Interaction Primitives with Phase Estimation

Jan Peters, Guilherme Maeda, Gerhard Neumann, 2015, ISRR.

Probabilistic movement primitives for coordination of multiple human–robot collaborative tasks

Oliver Kroemer, Jan Peters, Guilherme Maeda, 2017, Auton. Robots.

Phase estimation for fast action recognition and trajectory generation in human–robot collaboration

Jan Peters, Guilherme Maeda, Gerhard Neumann, 2017, Int. J. Robotics Res..

Probabilistic Prioritization of Movement Primitives

Jan Peters, Alexandros Paraschos, Gerhard Neumann, 2017, IEEE Robotics and Automation Letters.

Combining Human Demonstrations and Motion Planning for Movement Primitive Optimization

Jan Peters, Rudolf Lioutikov, Guilherme J. Maeda, 2016 .

Modeling Spatio-Temporal Variability in Human-Robot Interaction with Probabilistic Movement Primitives

Jan Peters, G. Neumann, Rudolf Lioutikov, 2015 .

Understanding Acoustic Patterns of Human Teachers Demonstrating Manipulation Tasks to Robots

A. Thomaz, Rudolf Lioutikov, S. Niekum, 2022, 2211.00352.

Probabilistic movement primitives for coordination of multiple human–robot collaborative tasks

Jan Peters, G. Neumann, Oliver Kroemer, 2016, Autonomous Robots.

Context-driven movement primitive adaptation

Jan Peters, Rudolf Lioutikov, Daniel Wilbers, 2017, 2017 IEEE International Conference on Robotics and Automation (ICRA).

Demonstration based trajectory optimization for generalizable robot motions

Jan Peters, Guilherme Maeda, Gerhard Neumann, 2016, 2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids).

Anticipative Interaction Primitives for Human-Robot Collaboration

Jan Peters, Guilherme Maeda, Marco Ewerton, 2016, AAAI Fall Symposia.

Learning interaction for collaborative tasks with probabilistic movement primitives

Jan Peters, Guilherme Maeda, Heni Ben Amor, 2014, 2014 IEEE-RAS International Conference on Humanoid Robots.

Learning attribute grammars for movement primitive sequencing

Jan Peters, Guilherme Maeda, Filipe Veiga, 2019, Int. J. Robotics Res..

Inducing Probabilistic Context-Free Grammars for the Sequencing of Movement Primitives

Kristian Kersting, Jan Peters, Guilherme Maeda, 2018, 2018 IEEE International Conference on Robotics and Automation (ICRA).

Inducing Probabilistic Context-Free Grammars for the Sequencing of Robot Movement Primitives

Kristian Kersting, Jan Peters, Guilherme Maeda, 2018 .

Self-Supervised Online Reward Shaping in Sparse-Reward Environments

Rudolf Lioutikov, S. Niekum, F. Memarian, 2021, 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Learning movement primitive libraries through probabilistic segmentation

Jan Peters, Guilherme Maeda, Gerhard Neumann, 2017, Int. J. Robotics Res..

Probabilistic segmentation applied to an assembly task

Jan Peters, Guilherme Maeda, Gerhard Neumann, 2015, 2015 IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids).

Learning multiple collaborative tasks with a mixture of Interaction Primitives

Jan Peters, Guilherme Maeda, Heni Ben Amor, 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

Distributional Depth-Based Estimation of Object Articulation Models

Scott Niekum, Stephen Giguere, Rudolf Lioutikov, 2021, CoRL.

Goal-Conditioned Imitation Learning using Score-based Diffusion Policies

Rudolf Lioutikov, Xiaogang Jia, Moritz Reuss, 2023, ArXiv.

ScrewNet: Category-Independent Articulation Model Estimation From Depth Images Using Screw Theory

Scott Niekum, Rudolf Lioutikov, Ajinkya Jain, 2020, 2021 IEEE International Conference on Robotics and Automation (ICRA).

MP3: Movement Primitive-Based (Re-)Planning Policy

G. Neumann, Rudolf Lioutikov, Onur Çelik, 2023, 2306.12729.

ProDMPs: A Unified Perspective on Dynamic and Probabilistic Movement Primitives

Rudolf Lioutikov, Michael Volpp, U. Tuebingen, 2022, ArXiv.

Model-Based Relative Entropy Stochastic Search

Luís Paulo Reis, Nuno Lau, Gerhard Neumann, 2016, NIPS.

Guiding Trajectory Optimization by Demonstrated Distributions

Jan Peters, Gerhard Neumann, Rustam Stolkin, 2017, IEEE Robotics and Automation Letters.

Goal-Conditioned Imitation Learning using Score-based Diffusion Policies

Rudolf Lioutikov, Xiaogang Jia, Moritz Reuss, 2023, Robotics: Science and Systems.

Generalizing Movements with Information-Theoretic Stochastic Optimal Control

Jan Peters, Alexandros Paraschos, Gerhard Neumann, 2014, J. Aerosp. Inf. Syst..

Sample-based informationl-theoretic stochastic optimal control

Jan Peters, Alexandros Paraschos, Gerhard Neumann, 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

Curriculum-Based Imitation of Versatile Skills

G. Neumann, Rudolf Lioutikov, Onur Çelik, 2023, 2023 IEEE International Conference on Robotics and Automation (ICRA).

Information Maximizing Curriculum: A Curriculum-Based Approach for Training Mixtures of Experts

G. Neumann, Rudolf Lioutikov, Xiaogang Jia, 2023, ArXiv.

Machine learning and the brain

Rudolf Lioutikov, Sukhan Lee, E. Menegatti, 2012 .

Movement Primitive Diffusion: Learning Gentle Robotic Manipulation of Deformable Objects

Paul Maria Scheikl, Rudolf Lioutikov, Niklas Freymuth, 2023, 2312.10008.

MP3: Movement Primitive-Based (Re-)Planning Policy

G. Neumann, Rudolf Lioutikov, Onur Çelik, 2023, ArXiv.

ProDMP: A Unified Perspective on Dynamic and Probabilistic Movement Primitives

Rudolf Lioutikov, Michael Volpp, U. Tuebingen, 2023, IEEE Robotics and Automation Letters.

Variational Distillation of Diffusion Policies into Mixture of Experts

Rudolf Lioutikov, Onur Celik, Denis Blessing, 2024, ArXiv.

Towards Diverse Behaviors: A Benchmark for Imitation Learning with Human Demonstrations

Rudolf Lioutikov, Moritz Reuss, Denis Blessing, 2024, ICLR.