Interactive Learning


Giovanni Franzese, Leandro de Souza Rosa, Tim Verburg, Luka Peternel, and Jens Kober. Interactive Imitation Learning of Bimanual Movement Primitives. IEEE/ASME Transactions on Mechatronics, ():1–13, 2023. [bibtex] [doi] [code] [video] gold open access


Armin Avaei, Linda van der Spaa, Luka Peternel, and Jens Kober. An Incremental Inverse Reinforcement Learning Approach for Motion Planning with Separated Path and Velocity Preferences. Robotics, 12(2):61, 2023. [bibtex] [pdf] [doi] [video] gold open access


Carlos E. Celemin and Jens Kober. Knowledge- and Ambiguity-Aware Robot Learning from Corrective and Evaluative Feedback. Neural Computing and Applications, 35(23):16821–16839, 2023. [bibtex] [pdf] [doi] [code] [video] gold open access


Jelle Luijkx, Zlatan Ajanović, Laura Ferranti, and Jens Kober. PARTNR: Pick and place Ambiguity Resolving by Trustworthy iNteractive leaRning. In NeurIPS 2022 - 5th Robot Learning Workshop: Trustworthy Robotics, 2022. [bibtex] [pdf] [url] [webpage] [video] bronze open access


Mariano Ramirez Montero, Giovanni Franzese, Jeroen Zwanepol, and Jens Kober. Solving Robot Assembly Tasks by Combining Interactive Teaching and Self-Exploration. arXiv:2209.11530 [cs.RO], 2022. [bibtex] [pdf] [doi] [code] [video] bronze open access


Anna Mészáros, Giovanni Franzese, and Jens Kober. Learning to Pick at Non-Zero-Velocity From Interactive Demonstrations. IEEE Robotics and Automation Letters, 7(3):6052–6059, 2022. [bibtex] [pdf] [url] [doi] [video] gold open access


Giovanni Franzese, Anna Mészáros, Luka Peternel, and Jens Kober. ILoSA: Interactive Learning of Stiffness and Attractors. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 7778–7785, 2021. [bibtex] [pdf] [url] [doi] [code] [video] green open access


Snehal Jauhri, Carlos E. Celemin, and Jens Kober. Interactive Imitation Learning in State-Space. In 2020 Conference on Robot Learning (CoRL) (Jens Kober, Fabio Ramos, Claire Tomlin, eds.), PMLR, vol. 155 of Proceedings of Machine Learning Research, pp. 682–692, 2021. [bibtex] [pdf] [html] [code] [video] gold open access


Giovanni Franzese, Carlos E. Celemin, and Jens Kober. Learning Interactively to Resolve Ambiguity in Reference Frame Selection. In 2020 Conference on Robot Learning (CoRL) (Jens Kober, Fabio Ramos, Claire Tomlin, eds.), PMLR, vol. 155 of Proceedings of Machine Learning Research, pp. 1298–1311, 2021. [bibtex] [pdf] [html] [code] [video] gold open access


Rodrigo Pérez-Dattari, Carlos E. Celemin, Giovanni Franzese, Javier Ruiz-del-Solar, and Jens Kober. Interactive Learning of Temporal Features for Control: Shaping Policies and State Representations From Human Feedback. IEEE Robotics & Automation Magazine, 27(2):46–54, 2020. [bibtex] [pdf] [doi] [code] [video] green open access


Carlos E. Celemin, Guilherme Maeda, Javier Ruiz-del-Solar, Jan Peters, and Jens Kober. Reinforcement Learning of Motor Skills using Policy Search and Human Corrective Advice. International Journal of Robotics Research, 38(14):1560–1580, 2019. [bibtex] [pdf] [doi] [video] green open access


Carlos E. Celemin and Jens Kober. Simultaneous Learning of Objective Function and Policy from Interactive Teaching with Corrective Feedback. In IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), pp. 726–732, 2019. [bibtex] [pdf] [doi] [video] green open access


Rodrigo Pérez-Dattari, Carlos E. Celemin, Javier Ruiz-del-Solar, and Jens Kober. Continuous Control for High-Dimensional State Spaces: An Interactive Learning Approach. In IEEE International Conference on Robotics and Automation (ICRA), pp. 7611–7617, 2019. [bibtex] [pdf] [doi] [code] [video] green open access


Rodrigo Pérez-Dattari, Carlos E. Celemin, Javier Ruiz-del-Solar, and Jens Kober. Interactive Learning with Corrective Feedback for Policies based on Deep Neural Networks. In International Symposium on Experimental Robotics (ISER) (Jing Xiao, Torsten Kröger, Oussama Khatib, eds.), Springer International Publishing, pp. 353–363, 2018. [bibtex] [pdf] [doi] [code] [video] green open access


Carlos E. Celemin, Javier Ruiz-del-Solar, and Jens Kober. A Fast Hybrid Reinforcement Learning Framework with Human Corrective Feedback. Autonomous Robots, 43(5):1173–1186, 2019. [bibtex] [pdf] [doi] [video] gold open access