Probabilistic Movement Primitives A Paraschos, C Daniel, J Peters, G Neumann Advances in Neural Information Processing Systems (NIPS), 2013 | 715 | 2013 |
Using probabilistic movement primitives in robotics A Paraschos, C Daniel, J Peters, G Neumann Autonomous Robots 42 (3), 529-551, 2018 | 229 | 2018 |
Model-based imitation learning by probabilistic trajectory matching P Englert, A Paraschos, J Peters, MP Deisenroth Robotics and Automation (ICRA), 2013 IEEE International Conference on, 1922-1927, 2013 | 78 | 2013 |
Sample-Based Information-Theoretic Stochastic Optimal Control R Lioutikov, A Paraschos, J Peters, G Neumann | 78* | |
Probabilistic Model-based Imitation Learning P Englert, A Paraschos, J Peters, MP Deisenroth Adaptive Behavior 21, 388-403, 2013 | 65 | 2013 |
Extracting low-dimensional control variables for movement primitives E Rueckert, J Mundo, A Paraschos, J Peters, G Neumann Robotics and Automation (ICRA), 2015 IEEE International Conference on, 1511-1518, 2015 | 48 | 2015 |
Model-driven behavior specification for robotic teams A Paraschos, NI Spanoudakis, MG Lagoudakis Proceedings of the 11th International Conference on Autonomous Agents and …, 2012 | 40 | 2012 |
Constrained Probabilistic Movement Primitives for Robot Trajectory Adaptation F Frank, A Paraschos, P van der Smagt, B Cseke arXiv preprint arXiv:2101.12561, 2021 | 39 | 2021 |
Prediction of intention during interaction with ICUB with probabilistic movement primitives O Dermy, A Paraschos, M Ewerton, J Peters, F Charpillet, S Ivaldi Frontiers in Robotics and AI 4, 45, 2017 | 34 | 2017 |
Probabilistic prioritization of movement primitives A Paraschos, R Lioutikov, J Peters, G Neumann IEEE Robotics and Automation Letters, 2017 | 31 | 2017 |
Learning Modular Policies for Robotics G Neumann, C Daniel, A Paraschos, A Kupcsik, J Peters Frontiers in Computational Neuroscience 8, 62, 2014 | 29 | 2014 |
Fast approximate geodesics for deep generative models N Chen, F Ferroni, A Klushyn, A Paraschos, J Bayer, P van der Smagt International Conference on Artificial Neural Networks, 554-566, 2019 | 27 | 2019 |
Probabilistic movement primitives under unknown system dynamics A Paraschos, E Rueckert, J Peters, G Neumann Advanced Robotics 32 (6), 297-310, 2018 | 24 | 2018 |
Model-free Probabilistic Movement Primitives for physical interaction A Paraschos, E Rueckert, J Peters, G Neumann Intelligent Robots and Systems (IROS), 2015 IEEE/RSJ International …, 2015 | 24 | 2015 |
A Probabilistic Approach to Robot Trajectory Generation A Paraschos, G Neumann, J Peters Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), 2013 | 22 | 2013 |
Reinforcement learning vs human programming in tetherball robot games S Parisi, H Abdulsamad, A Paraschos, C Daniel, J Peters Intelligent Robots and Systems (IROS), 2015 IEEE/RSJ International …, 2015 | 20 | 2015 |
Active learning based on data uncertainty and model sensitivity N Chen, A Klushyn, A Paraschos, D Benbouzid, P Van der Smagt 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2018 | 16 | 2018 |
Monas: A flexible software architecture for robotic agents A Paraschos Diploma thesis, Technical University of Crete, Greece 29, 43-71, 2010 | 10 | 2010 |
ORC—a lightweight, lightning-fast middleware F Frank, A Paraschos, P van der Smagt 2019 Third IEEE International Conference on Robotic Computing (IRC), 337-343, 2019 | 5 | 2019 |
A Force-Distance Model of Humanoid Arm Withdrawal Reflexes T Dahl, A Paraschos Advances in Autonomous Robotics, 13-24, 2012 | 4 | 2012 |