Teaching Robots Interactively

Disagreement-Aware Variable Impedance Control for Online Learning of Physical Human-Robot Cooperation Tasks

Autori: Linda van der Spaa, Giovanni Franzese, Jens Kober, Michael Gienger
Pubblicato in: ICRA 2022 full day workshop - Shared Autonomy in Physical Human-Robot Interaction: Adaptability and Trust, 2022
Editore: workshop homepage

Interactive Learning of Sensor Policy Fusion

Autori: Bart Bootsma, Giovanni Franzese, Jens Kober
Pubblicato in: IEEE International Conference on Robot & Human Interactive Communication (RO-MAN), 2021
Editore: IEEE

Interactive Imitation Learning in State-Space

Autori: Snehal Jauhri, Carlos E. Celemin, Jens Kober
Pubblicato in: Conference on Robot Learning (CoRL), 2020
Editore: Proceedings of Machine Learning Research

Deep Reinforcement Learning with Feedback-based Exploration

Autori: Jan Scholten, Daan Wout, Carlos Celemin, Jens Kober
Pubblicato in: 2019 IEEE 58th Conference on Decision and Control (CDC), 2019, Pagina/e 803-808, ISBN 978-1-7281-1398-2
Editore: IEEE
DOI: 10.1109/cdc40024.2019.9029503

ILoSA: Interactive Learning of Stiffness and Attractors

Autori: Giovanni Franzese, Anna Mészáros, Luka Peternel, Jens Kober
Pubblicato in: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021
Editore: IEEE

Uncertainties Based Queries for Interactive Policy Learning with Evaluations and Corrections

Autori: Carlos Celemin, Jens Kober
Pubblicato in: ICMI '21 Companion, 2021
Editore: ACM
DOI: 10.1145/3461615.3485404

Learning from Few Demonstrations with Frame-Weighted Motion Generation

Autori: Jianyong Sun, Jihong Zhu, Jens Kober, and Michael Gienger
Pubblicato in: 18th International Symposium on Experimental Robotics (ISER), 2023
Editore: Springer

Learning Interactively to Resolve Ambiguity in Reference Frame Selection

Autori: Giovanni Franzese, Carlos E. Celemin, Jens Kober
Pubblicato in: Conference on Robot Learning (CoRL), 2020
Editore: Proceedings of Machine Learning Research

Robotic Packaging Optimization with Reinforcement Learning

Autori: Drijver, Eveline; Pérez-Dattari, Rodrigo; Kober, Jens; Della Santina, Cosimo; Ajanović, Zlatan
Pubblicato in: IEEE International Conference on Automation Science and Engineering (CASE), Numero 1, 2023
Editore: IEEE
DOI: 10.1109/case56687.2023.10260406

Value Function Learning via Prolonged Backward Heuristic Search

Autori: Zlatan Ajanović, Bakir Lačević, Jens Kober
Pubblicato in: ICAPS 2023 Workshop: PRL Workshop Series – Bridging the Gap Between AI Planning and Reinforcement Learning, 2023
Editore: workshop homepage

PARTNR: Pick and place Ambiguity Resolving by Trustworthy iNteractive leaRning

Autori: Jelle Luijkx, Zlatan Ajanović, Laura Ferranti, Jens Kober
Pubblicato in: NeurIPS 2022 - 5th Robot Learning Workshop: Trustworthy Robotics, 2022
Editore: WS homepage
DOI: 10.48550/arxiv.2211.08304

Robotic Fabric Flattening with Wrinkle Direction Detection

Autori: Yulei Qiu, Jihong Zhu, Cosimo Della Santina, Michael Gienger, and Jens Kober
Pubblicato in: 18th International Symposium on Experimental Robotics (ISER), 2023
Editore: Springer

Vision for Bosnia and Herzegovina in Artificial Intelligence Age: Global Trends, Potential Opportunities, Selected Use-cases and Realistic Goals \\ BOS: Vizija Bosne i Hercegovine u Doba Umjetne Inteligencije: Svjetski Trendovi, Mogućnosti, Odabrani Primjeri i Realistični Ciljevi

Autori: Zlatan Ajanović, Emina Aličković, Aida Branković, Sead Delalić, Eldar Kurtić, Salem Malikić, Adnan Mehonić, Hamza Merzić, Kenan Šehić, Bahrudin Trbalić
Pubblicato in: "Scientific-Professional Conference ""Artificial Intelligence in Bosnia and Herzegovina""- research, application and development perspectives, Federalno ministarstvo obrazovanja i nauke/znanosti : Fondacija za inovacijski i tehnološki razvoj", 2022, Pagina/e 13–46, ISBN 978-9958-11-165-5
Editore: Mostar : Federalno ministarstvo obrazovanja i nauke/znanosti : Fondacija za inovacijski i tehnološki razvoj, 2022 (Mostar : Print Team)

Damping Design for Robot Manipulators

Autori: Tomás Coleman, Giovanni Franzese, Pablo Borja
Pubblicato in: Human-Friendly Robotics 2022, 2023, Pagina/e 74–89
Editore: Springer International Publishing
DOI: 10.1007/978-3-031-22731-8_6

An Incremental Inverse Reinforcement Learning Approach for Motion Planning with Separated Path and Velocity Preferences

Autori: Armin Avaei; Linda van der Spaa; Luka Peternel; Jens Kober
Pubblicato in: Robotics, Numero VOLUME=12;ISSUE=2;, 2023, Pagina/e 61, ISSN 2218-6581
Editore: MDPI
DOI: 10.3390/robotics12020061

Adaptation Through Prediction: Multisensory Active Inference Torque Control

Autori: Cristian Meo, Giovanni Franzese, Corrado Pezzato, Max Spahn, Pablo Lanillos
Pubblicato in: IEEE Transactions on Cognitive and Developmental Systems, Numero 15(1), 2023, Pagina/e 32–41, ISSN 2379-8939
Editore: IEEE
DOI: 10.1109/tcds.2022.3156664

Learning to Pick at Non-Zero-Velocity from Interactive Demonstrations

Autori: Anna Mészáros, Giovanni Franzese, Jens Kober
Pubblicato in: IEEE Robotics and Automation Letters, 2022, ISSN 2377-3766
Editore: IEEE
DOI: 10.1109/lra.2022.3165531

Do You Need a Hand? - A Bimanual Robotic Dressing Assistance Scheme

Autori: Jihong Zhu, Michael Gienger, Giovanni Franzese, Jens Kober
Pubblicato in: IEEE Transactions on Robotics, Numero Vol 40, 2024, Pagina/e 1906-1919, ISSN 1552-3098
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tro.2024.3366008

Neural Optimal Control for Constrained Visual Servoing via Learning From Demonstration

Autori: Ravi Prakash, Laxmidhar Behera
Pubblicato in: IEEE Transactions on Automation Science and Engineering, 2023, ISSN 1545-5955
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tase.2023.3272739

Knowledge- and Ambiguity-Aware Robot Learning from Corrective and Evaluative Feedback

Autori: Carlos E. Celemin, Jens Kober
Pubblicato in: Neural Computing and Applications, Numero 35(23), 2023, Pagina/e 16821–16839, ISSN 0941-0643
Editore: Springer Verlag
DOI: 10.1007/s00521-022-08118-z

Interactive Learning of Temporal Features for Control: Shaping Policies and State Representations From Human Feedback

Autori: Rodrigo Perez-Dattari, Carlos Celemin, Giovanni Franzese, Javier Ruiz-del-Solar, Jens Kober
Pubblicato in: IEEE Robotics & Automation Magazine, Numero 27/2, 2020, Pagina/e 46-54, ISSN 1070-9932
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/mra.2020.2983649

Interactive Imitation Learning in Robotics: A Survey

Autori: Carlos Celemin, Rodrigo Pérez-Dattari, Eugenio Chisari, Giovanni Franzese, Leandro de Souza Rosa, Ravi Prakash, Zlatan Ajanović, Marta Ferraz, Abhinav Valada, and Jens Kober
Pubblicato in: Foundations and Trends® in Robotics, Numero 10(1–2), 2022, Pagina/e 1–197, ISSN 1935-8253
Editore: now publishers inc.
DOI: 10.1561/2300000072

Interactive Imitation Learning of Bimanual Movement Primitives

Autori: Giovanni Franzese, Leandro de Souza Rosa, Tim Verburg, Luka Peternel, and Jens Kober
Pubblicato in: IEEE/ASME Transactions on Mechatronics, 2023, ISSN 1083-4435
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tmech.2023.3295249

Solving Robot Assembly Tasks by Combining Interactive Teaching and Self-Exploration

Autori: Mariano Ramirez Montero, Giovanni Franzese, Jeroen Zwanepol, and Jens Kober
Pubblicato in: arxiv, 2022
Editore: arxiv
DOI: 10.48550/arxiv.2209.11530

Learning Gaussian Policies from Corrective Human Feedback

Autori: Daan Wout, Jan Scholten, Carlos Celemin, Jens Kober
Pubblicato in: arXiv, 2019
Editore: arXiv

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