Rudolf Lioutikov
Curriculum VitæResearch Interest
Machine-Learning: Imitation Learning, Reinforcement Learning, Optimal
Decision Making, Policy Search, Explainable AI, Skill and Behavior Representation, Skill Acquisition, Movement Segmentation, Structure Learning, Skill
Composition and Sequencing, Life-Long Learning, Active Learning
Robotics: Intuitive Robots, Anthropomorphic Robots, Human-Robot Interaction,
Semi-Autonomy, Motor Skills, Movement Primitive Representation, Grasping,
Manipulation, Adaptive Control, Human-In-The-Loop, Multi-Agent Systems,
Robot Assisted Rehabilitation, Intelligent Prosthetics

Current Position
12.2022 –Tenure-Track Professor for Machine Learning and Robotics, Intuitive
Robots Lab, Karlsruhe Intitute of Technology
Karlsruhe, Baden-Württemberg, Germany

Past Positions
06.2021 – 11.2022 Emmy-Noether Research Group Leader, Intuitive Robots Lab, Karlsruhe
Intitute of Technology
Karlsruhe, Baden-Württemberg, Germany

01.2019 – 05.2021 Assistant Professor of Practice, Texas Institute for Discovery Education in
Science, College of Natural Sciences, University of Texas at Austin
Austin, Texas, USA

Education
10.2013 – 10.2018 Ph.D. Student, Intelligent Autonomous Systems, Technical University Darmstadt, Darmstadt, Germany
Graduated with highest distinction / summa cum laude

08.2015 – 09.2015 Summer School, Machine Learning Summer School, Kyoto, Japan
10.2011 – 09.2013 M.Sc. in Computer Science, Technical University Darmstadt, Darmstadt,
Germany
Focus on Robotics and Machine Learning. Minor in Bionics.

07.2010 – 09.2011 Exchange, National University of the Province Buenos Aires, Tandil, Argentina
10.2006 – 07.2010 B.Sc. in Computer Science, Technical University Darmstadt, Darmstadt,
Germany

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Honors and Awards
2020 Accepted into the Emmy-Noether Programme of the German Research Foundation (DFG)
2019 Georges Giralt Award Finalist, European Robotics Forum grants this award forbest European robotics Ph.D. thesis
2015 Best Paper Award Finalist, IEEE International Conference on Robotics andAutomation (ICRA)Best Student Paper Award Finalist, IEEE International Conference on Robotics
and Automation (ICRA)Best Service Robotics Paper Award Finalist, IEEE International Conference on
Robotics and Automation (ICRA)

Grants2020 Intuitive Robot Intelligence, Emmy-Noether Programme of the German
Research Foundation (DFG)

Research Experience
11.2022 –Tenure-Track Professor for Machine Learning and Robotics, Intuitive
Robots Lab, Karlsruhe Intitute of Technology
Karlsruhe, Baden-Württemberg, Germany

06.2021 – 11.2022 Research Group Leader, Intuitive Robots Lab, Karlsruhe Intitute of Technology
Karlsruhe, Baden-Württemberg, Germany

01.2019 – 05.2021 Assistant Professor of Practice, Texas Institute for Discovery Education in
Science, College of Natural Sciences, University of Texas at Austin
Austin, Texas, USA

10.2013 – 10.2018 Graduate Research Assistant, Intelligent Autonomous Systems - Technical
University Darmstadt, Developing new methods to introduce robotics into small
and medium sized enterprises
3rd Hand Project - Seventh Framework Programme (FP7-ICT-2013-10)

09.2012 – 09.2013 Undergraduate Research Assistant, Intelligent Autonomous Systems - Technical University Darmstadt, Evaluation of robot learning methods on a throwing
scenario

Teaching Experience04.2024 –TT.-Professor, Advanced Artificial Intelligence, Karlsruhe Institute Of Technology

10.2023 –TT.-Professor, Deep Reinforcement Learning, Karlsruhe Institute Of Technology

12.2022 –TT.-Professor, Explainable Artificial Intelligence, Karlsruhe Institute Of
Technology

01.2019 – 05.2021 Assistant Professor, Robot Learning, University of Texas at Austin
10.2015 – 04.2016 Teaching Assistant, Robot Learning, Technical University Darmstadt

Building 50.19, Room 430 – Adenauerring 12 – 76131 Karlsruhe, BW, Germany
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04.2015 – 10.2015 Teaching Assistant, Intelligent Multi-Agent Systems, Technical University
Darmstadt
10.2014 – 04.2015 Teaching Assistant, Technical Foundations of Computer Science, Technical
University Darmstadt
04.2013 – 09.2013 Lecture Assistant, Software Engineering Design and Construction, Technical
University Darmstadt

Student Supervision
07.2024 –Ph.D., Leveraging Foundation Models in Human-Robot Interactions, Karlsruhe
Institute of Technology, Blank, N.

11.2023 –Ph.D., Autonomous Information Selection in Multisensory settings, Karlsruhe
Institute of Technology, Vanjani, P.

07.2023 –Ph.D., Affordance-Graphs as Interpretable High-Level Task and Behavior
Description, Karlsruhe Institute of Technology, Mattes, P.

12.2023 –Ph.D., Leveraging Extended Reality in Human-Robot Interaciton, Karlsruhe
Institute of Technology, Jiang, X.

12.2023 –Ph.D., Learning Multimodal Behavior through Imitation Learning, Karlsruhe
Institute of Technology, Jia, X.

10.2022 –Ph.D., Efficient and Interpretable Low-Level Behavior through Episodic Reinforcement Learning and Movement Primitives, Karlsruhe Institute of Technology,
Zhou, H.

07.2022 –Ph.D., Learning Interpretable Behavior through latent Prototypes, Karlsruhe
Institute of Technology, Li, M.

01.2022 –Ph.D., Learning Multimodal Behavior from Unstructured Demonstrations,Karlsruhe Institute of Technology, Reuss, M.

07.2019 – 08.2019 FRI Fellowship, Self-Supervised Semantic Grounding of Movement Primitive
Sequences, University of Texas at Austin, Bhave, S.; Kodali, P.; O’Neil, C.;
Trowbridge, I
07.2019 – 08.2019 FRI Fellowship, Self-Supervised Segmentation of Movement Primitive Sequences, University of Texas at Austin, Bhave, R.; Hao, K.; Thomson, I
04.2017 – 10.2017 Student Research Project, Learning Grammars for Sequencing Movement
Primitives, Technical University Darmstadt, Berninger, K.; Szelag, S
10.2016 – 04.2017 Student Research Project, Probabilistic Trajectory Segmentation by Means of
Hierarchical Dirichlet Process Switching Linear Dynamical Systems, Technical
University Darmstadt, Sieb, M.; Schultheis, M.; Szelag, S
01.2016 – 07.2016 Master’s Thesis, Context-driven Movement Primitive Adaptation, Technical
University Darmstadt, Wilbers, D
10.2015 – 04.2016 Master’s Thesis, Combining Human Demonstrations and Motion Planning for
Movement Primitive Optimization, Technical University Darmstadt, Koert, D
04.2014 – 04.2015 Student Research Project, Inverse Kinematics for Optimal Human-robot
Collaboration, Technical University Darmstadt, Koert, D
04.2014 – 04.2015 Student Research Project, Sequencing of Movement Primitives for Task- andMotion Planning , Technical University Darmstadt, Sigg M,; Faller, F
10.2013 – 04.2014 Student Research Project, Competitive Robot Pong, Technical University
Darmstadt, Koert, D.; Vandommele, T
Building 50.19, Room 430 – Adenauerring 12 – 76131 Karlsruhe, BW, Germany
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Workshop Organization
2024 2nd Workshop on Learning Effective Abstractions for Planning (LEAP), 8th
Annual Conference on Robot Learning, Co-Organizer
2021 Empowering Interactive Robots by Learning Through Multimodal Feedback
Channels, 23rd ACM International Conference on Multimodal Interaction,
Co-Organizer

Research Community Contribution
2024 Associate Editor IEEE Robotics and Automation Letters
Area Chair Robotics: Science and Systems
Area Chair Conference on Robot Learning
Area Chair The IEEE/RSJ International Conference on Intelligent Robots andSystems
2023 Associate Editor IEEE Robotics and Automation Letters
Area Chair Conference on Robot Learning
Area Chair The IEEE/RSJ International Conference on Intelligent Robots andSystems
2022 Associate Editor IEEE Robotics and Automation Letters
Area Chair Conference on Robot Learning
Area Chair The IEEE/RSJ International Conference on Intelligent Robots andSystems
2021 Associate Editor IEEE Robotics and Automation Letters
Area Chair Conference on Robot Learning
Area Chair The IEEE/RSJ International Conference on Intelligent Robots andSystems
2020
2019
2018
2017

2016

2015

The IEEE International Conference on Robotics and Automation
Conference on Robot Learning
AAAI Conference on Artificial Intelligence
Advances in Neural Information Processing Systems
Conference on Robot Learning
The IEEE/RSJ International Conference on Intelligent Robots and Systems
The IEEE Robotics and Automation Letters
The IEEE International Conference on Robotics and Automation
The IEEE Robotics and Automation Letters
The IEEE/RSJ International Conference on Intelligent Robots and Systems
The IEEE International Conference on Robotics and Automation
The International Journal of Robotics Research
The IEEE/RSJ International Conference on Intelligent Robots and Systems
The 25th International Joint Conference on Artificial Intelligence
Automatica
Autonomously Learning Robots Workshop at Advances in Neural Information
Processing Systems

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The IEEE/RSJ International Conference on Intelligent Robots and Systems
2014 The IEEE/RSJ International Conference on Intelligent Robots and Systems

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Publications
Ph.D. Thesis
2018 • Lioutikov, R., Parsing Motion and Composing Behavior for Semi-Autonomous
Manipulation,
Intelligent Autonomous Systems - Technical University Darmstadt,
Thesis Advisor: Prof. Dr. Jan Peters, Ph.D
External Referee: Prof. Ken Goldberg (UC Berkeley)Committee: Prof. Andreas Koch (TU Darmstadt),
Prof. Oskar von Stryk (TU Darmstadt),
Prof. Kristian Kersting (TU Darmstadt)

Master’s Thesis
2013 • Lioutikov, R., Learning time-dependent feedback policies with model-based
policy search, Intelligent Autonomous Systems - Technical University Darmstadt,
Thesis Advisors: Dr. tech. Gerhard Neumann, Prof. Dr. Jan Peters, Ph.D

Journal Articles
2024 • Scheikl, P.; Schreiber, N.; Haas, C.; Freymuth, N.; Neumann, G.; Lioutikov,
R.; Mathis-Ullrich, F., Movement Primitive Diffusion: Learning Gentle Robotic
Manipulation of Deformable Objects, IEEE Robotics and Automation Letters(RA-L)
2023 • Li, G.; Jin, Z.; Volpp, M.; Otto, F.; Lioutikov, R.; Neumann, G., ProDMP: A
Unified Perspective on Dynamic and Probabilistic Movement Primitives, IEEE
Robotics and Automation Letters (RA-L)
2019 • Lioutikov, R.; Maeda, G.; Veiga, F.F.; Kersting, K.; Peters, J., Learning
Attribute Grammars for Movement Primitive Sequencing, International Journalof Robotics Research (IJRR)
2017 • Lioutikov, R.; Neumann, G.; Maeda, G.; Peters, J., Learning Movement
Primitive Libraries through Probabilistic Segmentation, International Journal of
Robotics Research (IJRR)• Maeda, G.; Neumann, G.; Ewerton, M; Lioutikov, R.; Kroemer, O; Peters, J.,
Probabilistic Movement Primitives for Coordination of Multiple Human-Robot
Collaborative Tasks, Autonomous Robots (AURO)• Maeda, G.; Ewerton, M.; Neumann, G.; Lioutikov, R.; Peters, J., Phase Estimation for Fast Action Recognition and Trajectory Generation in Human-Robot
Collaboration, International Journal of Robotics Research (IJRR)• Osa, T.; Ghalamzan, E. A. M.; Stolkin, R.; Lioutikov, R.; Peters, J.; Neumann, G., Guiding Trajectory Optimization by Demonstrated Distributions, IEEE
Robotics and Automation Letters (RA-L)• Paraschos, A.; Lioutikov, R.; Peters, J.; Neumann, G., Probabilistic Prioritization of Movement Primitives, Proceedings of the International Conference onIntelligent Robot Systems, and IEEE Robotics and Automation Letters (RA-L)

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2014 • Lioutikov, R.; Paraschos, A.; Peters, J.; Neumann, G., Generalizing Movements with Information Theoretic Stochastic Optimal Control, Journal of
Aerospace Information Systems (JAIS)

Articles in Conference Proceedings
2024 • Blank, N.; Reuss, M.; Rühle, M.; Yamurlu, Ö.; Wenzel, F.; Mees, O.; Lioutikov, R., Scaling Robot Policy Learning via Zero-Shot Labeling withFoundation Models, 8th Annual Conference on Robot Learning (CoRL)• Jia, X.; Wang, Q.; Donat, A.; Xing, B.; Li, G.; Zhou, H.; Celik, O.; Blessing,D.; Lioutikov, R.; Neumann, G., MaIL: Improving Imitation Learning with
Selective State Space Models, 8th Annual Conference on Robot Learning (CoRL)• Reuss, M.; Yamurlu, Ö.; Wenzel, F.; Lioutikov, R., Multimodal Diffusion
Transformer: Learning Versatile Behavior from Multimodal Goals, Robotics:
Science and Systems XX (RSS)• Li, G.; Zhou, H.; Roth, D.; Thilges, S.; Otto, F.; Lioutikov, R.; Neumann,G., Open the Black Box: Step-based Policy Updates for Temporally-Correlated
Episodic Reinforcement Learning, The Twelfth International Conference on
Learning Representations (ICLR)• Jia, X.; Blessing, D.; Jiang, X.; Reuss, M.; Donat, A.; Lioutikov, R.; Neumann, G., Towards Diverse Behaviors: A Benchmark for Imitation Learningwith Human Demonstrations, The Twelfth International Conference on Learning
Representations (ICLR)• Jiang, X.; Mattes, P.; Jia, X.; Schreiber, N.; Neumann, G.; Lioutikov, R.,
A Comprehensive User Study on Augmented Reality-Based Data Collection
Interfaces for Robot Learning, Proceedings of the 2024 ACM/IEEE International
Conference on Human-Robot Interaction (HRI)
2023 • Blessing, D.; Celik, O.; Jia, X.; Reuss, M.; Li, M.; Lioutikov, R.; Neumann,G., Information Maximizing Curriculum: A Curriculum-Based Approach for
Learning Versatile Skills, Advances in Neural Information Processing Systems(NeurIPS)• Reuss, M.; Li, M.; Jia, X.; Lioutikov, R., Goal-Conditioned Imitation Learning
Using Score-based Diffusion Policies, Robotics: Science and Systems XIX (RSS)• Li, M.; Celik, O.; Becker, P.; Blessing, D.; Lioutikov, R.; Neumann, G.,
Curriculum-Based Imitation of Versatile Skills, 2023 IEEE International Conference on Robotics and Automation (ICRA)
2022 • Saran, A.; Desai, K.; Chang, M. L.; Lioutikov, R.; Thomaz, A.; Niekum, S.,
Understanding Acoustic Patterns of Human Teachers Demonstrating Tasks to
Robots, International Conference on Intelligent Robots and Systems (IROS)• Li, M.; Celik. O.; Becker, P.; Blessing, D.; Lioutikov, R.; Neumann, G.,
Curriculum-Based Imitation of Versatile Skills, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)
2021 • Jain, A.; Lioutikov, R.; Giguere, S.; Niekum, S., Distributional Depth-Based
Estimation of Object Articulation Models, Conference on Robot Learning(CoRL)

Building 50.19, Room 430 – Adenauerring 12 – 76131 Karlsruhe, BW, Germany
MOBILE-ALT +49 1515 610 4480 • Envelope lioutikov@kit.edu • GLOBE-AMERICAS https://rudolf.intuitive-robots.net/

Page 7 of 10• Jain, A.; Lioutikov, R.; Chuck, C.; Niekum, S., ScrewNet: CategoryIndependent Articulation Model Estimation From DepthImages Using Screw
Theory, Proceedings of the IEEE International Conference on Robotics andAutomation (ICRA)• Memarian, F.; Goo, W.; Lioutikov, R.; Topcu, U.; Niekum, S., SelfSupervised Online Reward Shaping in Sparse-Reward Environments, International
Conference on Intelligent Robots and Systems (IROS)
2018 • Lioutikov, R.; Maeda, G.; Veiga, F.F.; Kersting, K.; Peters, J., Inducing
Probabilistic Context-Free Grammars for the Sequencing of Robot Movement
Primitives, Proceedings of the IEEE International Conference on Robotics andAutomation (ICRA)
2017 • Wilbers, D.; Lioutikov, R.; Peters, J., Context-Driven Movement Primitive
Adaptation, Proceedings of the IEEE International Conference on Robotics andAutomation (ICRA)
2016 • Maeda, G.; Maloo, A.; Ewerton, M.; Lioutikov, R.; Peters, J., Anticipative
Interaction Primitives for Human-Robot Collaboration, AAAI Fall Symposium
Series. Shared Autonomy in Research and Practice• Koert, D.; Maeda, G.J.; Lioutikov, R.; Neumann, G.; Peters, J., Demonstration Based Trajectory Optimization for Generalizable Robot Motions, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS)
2015 • Lioutikov, R.; Neumann, G.; Maeda, G.; Peters, J., Probabilistic Segmentation Applied to an Assembly Task, Proceedings of the International Conferenceon Humanoid Robots (HUMANOIDS)• Ewerton, M; Maeda, G; Lioutikov, R.; Amor, H.B.; Peters J.; Neumann, G.,
Learning Multiple Collaborative Tasks with a Mixture of Interaction Primitives,
IEEE International Conference on Robotics and Automation (ICRA)Best Conference Paper Award Finalist, Best Student Paper Award Finalist, Best Service
Robotics Paper Award Finalist• Maeda, G.; Neumann, G.; Ewerton, M.; Lioutikov, R.; Peters, J., A Probabilistic Framework for Semi-Autonomous Robots Based on Interaction Primitives
with Phase Estimation, Proceedings of the International Symposium of Robotics
Research (ISRR)• Abdolmaleki, A.; Lioutikov, R.; Peters, J; Lau, N.; Reis, L.; Neumann,G., Model-Based Relative Entropy Stochastic Search, Advances in Neural
Information Processing Systems (NIPS)
2014 • Lioutikov, R.; Paraschos, A.; Peters, J.; Neumann, G., Sample-BasedInformation-Theoretic Stochastic Optimal Control, Proceedings of the IEEE
International Conference on Robotics and Automation (ICRA)• Lioutikov, R.; Kroemer, O.; Peters, J.; Maeda, G., Learning Manipulation by
Sequencing Motor Primitives with a Two-Armed Robot, Proceedings of the 13th
International Conference on Intelligent Autonomous Systems (IAS)• Maeda, G.J.; Ewerton, M.; Lioutikov, R.; Amor, H.B.; Peters, J.; Neumann,G., Learning Interaction for Collaborative Tasks with Probabilistic Movement
Primitives, Proceedings of the International Conference on Humanoid Robots(HUMANOIDS)

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Workshop papers
2024 • Blank, N.; Reuss, M.; Wenzel, F.; Mees, O.; Lioutikov, R., Scaling Robot
Policy Learning via Zero-Shot Labeling with Foundation Models, ICRA 2024
Workshop on 3D Visual Representations for Robot Manipulation• Li, G.; Zhou, H.; Roth, D.; Thilges, S.; Otto, F.; Lioutikov, R.; Neumann, G.,
Latent Space Exploration and Trajectory Space Update in Temporally-Correlated
Episodic Reinforcement Learning, Back to the Future: Robot Learning Going
Probabilistic at ICRA
• Reuss, M.; Yamurlu, Ö.; Wenzel, F.; Lioutikov, R., Multimodal Diffusion
Transformer: Learning Versatile Behavior from Multimodal Goals, First Workshop on Vision-Language Models for Navigation and Manipulation at ICRA
• Reuss, M.; Pari, J.; Agrawal, P.; Lioutikov, R., Efficient Diffusion Transformer Policies with Mixture of Expert Denoisers for Multitask Learning, ICRA
2024 Workshop: A Future Roadmap for Sensorimotor Skill Learning for Robot
Manipulation• Jia, X.; Blessing, D.; Jiang, X.; Reuss, M.; Donat, A.; Lioutikov, R.; Neumann, G., Towards Diverse Behaviors: A Benchmark for Imitation Learningwith Human Demonstrations, ICRA 2024 Workshop: A Future Roadmap for
Sensorimotor Skill Learning for Robot Manipulation• Blank, N.; Reuss, M.; Wenzel, F.; Mees, O.; Lioutikov, R., Scaling Robot
Policy Learning via Zero-Shot Labeling with Foundation Models, ICRA 2024
Workshop: A Future Roadmap for Sensorimotor Skill Learning for Robot
Manipulation• Scheikl, P.M.; Schreiber, N.; Haas, C.; Freymuth, N.; Neumann, G.; Lioutikov,
R.; Mathis-Ullrich, F., Movement primitive diffusion: Learning gentle robotic
manipulation of deformable objects, ICRA 2024 Workshop: A Future Roadmap
for Sensorimotor Skill Learning for Robot Manipulation• Blank, N.; Reuss, M.; Wenzel, F.; Mees, O.; Lioutikov, R., Scaling Robot
Policy Learning via Zero-Shot Labeling with Foundation Models, 2nd Workshop
on Mobile Manipulation and Embodied Intelligence at ICRA 2024
• Reuss, M.; Yamurlu, Ö.E.; Wenzel, F.; Lioutikov, R., Multimodal Diffusion
Transformer: Learning Versatile Behavior from Multimodal Goals, First Workshop on Vision-Language Models for Navigation and Manipulation at ICRA
2024
2023 • Jiang, X.; Mattes, P.; Jia, X.; Neumann, G.; Lioutikov, R., A User Study on
Augmented Reality-Based Robot Learning Data Collection Interfaces, Towards
Generalist Robots: Learning Paradigms for Scalable Skill Acquisition at CoRL
• Reuss, M.; Lioutikov, R., Multimodal Diffusion Transformer for Learning from
Play, 2nd Workshop on Language and Robot Learning: Language as Groundingat CoRL• Zhou, H.; Otto, F.; Celik, O.; Li, G.; Lioutikov, R.; Neumann, G., MP3:
Movement Primitive-Based (Re-) Planning Policy, CoRL 2023 Workshop on
Learning Effective Abstractions for Planning (LEAP)2018 • Lioutikov, R.; Faller, F.; Sigg, M.; Perters, J.; Maeda, G., A Graph-Search
Based Approach for Movement Primitive Sequencing, Abstract-Only Session
IEEE International Conference on Robotics and Automation (ICRA)
Building 50.19, Room 430 – Adenauerring 12 – 76131 Karlsruhe, BW, Germany
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Page 9 of 10• Lioutikov, R.; Maeda, G.; Veiga, F.F.; Kersting, K.; Peters, J., Learning
Intuitive Grammars for Movement Primitive Sequences, Robot Teammates
Operating in Dynamic, Unstructured Environments
IEEE International Conference on Robotics and Automation (ICRA)• Lioutikov, R.; Perters, J., Movement Primitive Sequencing via Attribute
Grammars, Third Machine Learning in Planning and Control of Robot Motion
WorkshopIEEE International Conference on Robotics and Automation (ICRA)

2016 • Maeda, G.; Maloo, A.; Ewerton, M.; Lioutikov, R.; Peters, J., Proactive
Human-Robot Collaboration with Interaction Primitives, International Workshop
on Human-Friendly Robotics (HFR)
2015 • Lopes, M.; Peters, J.; Piater, J.; Toussaint, M.; Baisero, A.; Busch, B.; Erkent,O.; Kroemer, O.; Lioutikov, R.; Maeda, G.; Mollard, Y.; Munzer, T.; Shukla,
D., Semi-Autonomous 3rd-Hand Robot, Workshop on Cognitive Robotics inFuture Manufacturing Scenarios
European Robotics Forum• Rueckert, E.; Lioutikov, R.; Calandra, R.; Schmidt, M.; Beckerle, P.; Peters,J., Low-cost Sensor Glove with Force Feedback for Learning from Demonstrations using Probabilistic Trajectory Representations, Workshop on Tactile andforce sensing for autonomous compliant intelligent robots.
IEEE International Conference on Robotics and Automation (ICRA)

2014 • Lioutikov, R.; Kroemer, O.; Peters, J.; Maeda, G., Towards a Third Hand, 1stInternational Workshop on Intelligent Robot Assistants
International Conference on Intelligent Autonomous Systems (IAS)• Ewerton, M.; Neumann, G.; Lioutikov, R.; Amor, H.B.; Peters, J.; Maeda,G., Modeling Spatio-Temporal Variability in Human-Robot Interaction with
Probabilistic Movement Primitives, Workshop on Machine Learning for Social
Robotics
IEEE International Conference on Robotics and Automation (ICRA)

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