Publications

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2021

Tanneberg, Daniel; Ploeger, Kai; Rueckert, Elmar; Peters, Jan

SKID RAW: Skill Discovery from Raw Trajectories Journal Article

IEEE Robotics and Automation Letters (RA-L), pp. 1–8, 2021, ISSN: 2377-3766, (© 20XX IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.).

Links | BibTeX | Tags: Manipulation, movement primitives, Probabilistic Inference

SKID RAW: Skill Discovery from Raw Trajectories

Jamsek, Marko; Kunavar, Tjasa; Bobek, Urban; Rueckert, Elmar; Babic, Jan

Predictive exoskeleton control for arm-motion augmentation based on probabilistic movement primitives combined with a flow controller Journal Article

IEEE Robotics and Automation Letters (RA-L), pp. 1–8, 2021, ISSN: 2377-3766, (© 20XX IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.).

Links | BibTeX | Tags: human motor control, movement primitives

Predictive exoskeleton control for arm-motion augmentation based on probabilistic movement primitives combined with a flow controller

Cansev, Mehmet Ege; Xue, Honghu; Rottmann, Nils; Bliek, Adna; Miller, Luke E; Rueckert, Elmar; Beckerle, Philipp

Interactive Human-Robot Skill Transfer: A Review of Learning Methods and User Experience Journal Article

Advanced Intelligent Systems, pp. 1–28, 2021.

Links | BibTeX | Tags: human motor control, intrinsic motivation, movement primitives, Probabilistic Inference, Reinforcement Learning, spiking

Interactive Human-Robot Skill Transfer: A Review of Learning Methods and User Experience

2019

Stark, Svenja; Peters, Jan; Rueckert, Elmar

Experience Reuse with Probabilistic Movement Primitives Inproceedings

Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS), 2019., 2019.

Links | BibTeX | Tags: movement primitives, Reinforcement Learning, Transfer Learning

Experience Reuse with Probabilistic Movement Primitives

2018

Sosic, Adrian; Zoubir, Abdelhak M; Rueckert, Elmar; Peters, Jan; Koeppl, Heinz

Inverse Reinforcement Learning via Nonparametric Spatio-Temporal Subgoal Modeling Journal Article

Journal of Machine Learning Research (JMLR), 19 (69), pp. 1-45, 2018.

Links | BibTeX | Tags: movement primitives, Probabilistic Inference, Simulation

Inverse Reinforcement Learning via Nonparametric Spatio-Temporal Subgoal Modeling

Paraschos, Alexandros; Rueckert, Elmar; Peters, Jan; Neumann, Gerhard

Probabilistic Movement Primitives under Unknown System Dynamics Journal Article

Advanced Robotics (ARJ), 32 (6), pp. 297-310, 2018.

Links | BibTeX | Tags: inverse dynamics, model learning, movement primitives

Probabilistic Movement Primitives under Unknown System Dynamics

2017

Stark, Svenja; Peters, Jan; Rueckert, Elmar

A Comparison of Distance Measures for Learning Nonparametric Motor Skill Libraries Inproceedings

Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), 2017.

Links | BibTeX | Tags: intrinsic motivation, movement primitives

A Comparison of Distance Measures for Learning Nonparametric Motor Skill Libraries

2015

Rueckert, Elmar; Mundo, Jan; Paraschos, Alexandros; Peters, Jan; Neumann, Gerhard

Extracting Low-Dimensional Control Variables for Movement Primitives Inproceedings

Proceedings of the International Conference on Robotics and Automation (ICRA), 2015.

Links | BibTeX | Tags: movement primitives, Probabilistic Inference

Extracting Low-Dimensional Control Variables for Movement Primitives

Paraschos, Alexandros; Rueckert, Elmar; Peters, Jan; Neumann, Gerhard

Model-Free Probabilistic Movement Primitives for Physical Interaction Inproceedings

Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS), 2015.

Links | BibTeX | Tags: inverse dynamics, movement primitives

Model-Free Probabilistic Movement Primitives for Physical Interaction

2014

Rueckert, Elmar

Biologically inspired motor skill learning in robotics through probabilistic inference PhD Thesis

Technical University Graz, 2014.

Links | BibTeX | Tags: graphical models, locomotion, model learning, morphological compuation, movement primitives, policy search, postural control, Probabilistic Inference, Reinforcement Learning, RNN, SOC, spiking

Biologically inspired motor skill learning in robotics through probabilistic inference

2013

Rueckert, Elmar; d’Avella, Andrea

Learned parametrized dynamic movement primitives with shared synergies for controlling robotic and musculoskeletal systems Journal Article

Frontiers in Computational Neuroscience, 7 (138), 2013.

Links | BibTeX | Tags: locomotion, movement primitives, muscle synergies

Learned parametrized dynamic movement primitives with shared synergies for controlling robotic and musculoskeletal systems

Rueckert, Elmar; Neumann, Gerhard; Toussaint, Marc; Maass, Wolfgang

Learned graphical models for probabilistic planning provide a new class of movement primitives Journal Article

Frontiers in Computational Neuroscience, 6 (97), 2013.

Links | BibTeX | Tags: graphical models, movement primitives, Probabilistic Inference

 Learned graphical models for probabilistic planning provide a new class of movement primitives

Compact List without Images

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Journal Articles

Tanneberg, Daniel; Ploeger, Kai; Rueckert, Elmar; Peters, Jan

SKID RAW: Skill Discovery from Raw Trajectories Journal Article

IEEE Robotics and Automation Letters (RA-L), pp. 1–8, 2021, ISSN: 2377-3766, (© 20XX IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.).

Links | BibTeX

Jamsek, Marko; Kunavar, Tjasa; Bobek, Urban; Rueckert, Elmar; Babic, Jan

Predictive exoskeleton control for arm-motion augmentation based on probabilistic movement primitives combined with a flow controller Journal Article

IEEE Robotics and Automation Letters (RA-L), pp. 1–8, 2021, ISSN: 2377-3766, (© 20XX IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.).

Links | BibTeX

Cansev, Mehmet Ege; Xue, Honghu; Rottmann, Nils; Bliek, Adna; Miller, Luke E; Rueckert, Elmar; Beckerle, Philipp

Interactive Human-Robot Skill Transfer: A Review of Learning Methods and User Experience Journal Article

Advanced Intelligent Systems, pp. 1–28, 2021.

Links | BibTeX

Sosic, Adrian; Zoubir, Abdelhak M; Rueckert, Elmar; Peters, Jan; Koeppl, Heinz

Inverse Reinforcement Learning via Nonparametric Spatio-Temporal Subgoal Modeling Journal Article

Journal of Machine Learning Research (JMLR), 19 (69), pp. 1-45, 2018.

Links | BibTeX

Paraschos, Alexandros; Rueckert, Elmar; Peters, Jan; Neumann, Gerhard

Probabilistic Movement Primitives under Unknown System Dynamics Journal Article

Advanced Robotics (ARJ), 32 (6), pp. 297-310, 2018.

Links | BibTeX

Rueckert, Elmar; d’Avella, Andrea

Learned parametrized dynamic movement primitives with shared synergies for controlling robotic and musculoskeletal systems Journal Article

Frontiers in Computational Neuroscience, 7 (138), 2013.

Links | BibTeX

Rueckert, Elmar; Neumann, Gerhard; Toussaint, Marc; Maass, Wolfgang

Learned graphical models for probabilistic planning provide a new class of movement primitives Journal Article

Frontiers in Computational Neuroscience, 6 (97), 2013.

Links | BibTeX

Inproceedings

Stark, Svenja; Peters, Jan; Rueckert, Elmar

Experience Reuse with Probabilistic Movement Primitives Inproceedings

Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS), 2019., 2019.

Links | BibTeX

Stark, Svenja; Peters, Jan; Rueckert, Elmar

A Comparison of Distance Measures for Learning Nonparametric Motor Skill Libraries Inproceedings

Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), 2017.

Links | BibTeX

Rueckert, Elmar; Mundo, Jan; Paraschos, Alexandros; Peters, Jan; Neumann, Gerhard

Extracting Low-Dimensional Control Variables for Movement Primitives Inproceedings

Proceedings of the International Conference on Robotics and Automation (ICRA), 2015.

Links | BibTeX

Paraschos, Alexandros; Rueckert, Elmar; Peters, Jan; Neumann, Gerhard

Model-Free Probabilistic Movement Primitives for Physical Interaction Inproceedings

Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS), 2015.

Links | BibTeX

PhD Theses

Rueckert, Elmar

Biologically inspired motor skill learning in robotics through probabilistic inference PhD Thesis

Technical University Graz, 2014.

Links | BibTeX