Learning Physical Human-Robot Cooperation Tasks

example task

Project type

Industry project (Honda Research Institute Europe GmbH, HTSM PPS-toeslag); 2017-2022


Human-robot interaction and collaboration is of fundamental importance for any robot leaving the safety of fences on a highly-structured factory floor: service and care scenarios, medical applications, offshore, maintenance and inspection, as well as industrial assembly. In this project, we will develop new concepts and techniques for robot learning that endow robots with the capability to physically interact and collaborate with humans. In particular, we will consider tasks related to joint handling of large objects, i.e., jointly transporting and manipulating them. Examples include transporting and assembling light traverses, or changing tires on a car.

Project members

ir. Linda van der Spaa, ir. Tamas Bates, Dr. Jihong Zhu, Dr.-Ing. Jens Kober, Dr.-Ing. Michael Gienger

Publications with videos

Jihong Zhu, Michael Gienger, Giovanni Franzese, and Jens Kober. Do You Need a Hand? – An Interactive Robotic Dressing Assistance Scheme. arXiv:2301.02749 [cs.RO], 2023. [bibtex] [pdf] [url] [doi] [video]

Linda van der Spaa, Giovanni Franzese, Jens Kober, and Michael Gienger. Disagreement-Aware Variable Impedance Control for Online Learning of Physical Human-Robot Cooperation Tasks. In ICRA 2022 full day workshop - Shared Autonomy in Physical Human-Robot Interaction: Adaptability and Trust, 2022. [bibtex] [pdf] [code] [video]

Jihong Zhu, Michael Gienger, and Jens Kober. Learning Task-Parameterized Skills from Few Demonstrations. IEEE Robotics and Automation Letters, 2022. The contents of this paper were also selected by ICRA'22 Program Committee for presentation at the Conference. [bibtex] [pdf] [url] [doi] [code] [video]

Linda F. van der Spaa, Tamas Bates, Michael Gienger, and Jens Kober. Predicting and Optimizing Ergonomics in Physical Human-Robot Cooperation Tasks. In IEEE International Conference on Robotics and Automation (ICRA), pp. 1799–1805, 2020. [bibtex] [pdf] [doi] [video]

Michael Gienger, Dirk Ruiken, Tamas Bates, Mohamed Regaieg, Michael Meißner, Jens Kober, Philipp Seiwald, and Arne-Christoph Hildebrandt. Human-Robot Cooperative Object Manipulation with Contact Changes. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 1354–1360, 2018. [bibtex] [pdf] [doi] [video]

Publications without videos

Armin Avaei, Linda van der Spaa, Luka Peternel, and Jens Kober. An Incremental Inverse Reinforcement Learning Approach for Motion Planning with Human Preferences. arXiv:2301.10528 [cs.RO], 2023. [bibtex] [pdf] [doi] [video]

Jihong Zhu, Andrea Cherubini, Claire Dune, David Navarro-Alarcon, Farshid Alambeigi, Dmitry Berenson, Fanny Ficuciello, Kensuke Harada, Jens Kober, Xiang Li, Jia Pan, Wenzhen Yuan, and Michael Gienger. Challenges and Outlook in Robotic Manipulation of Deformable Objects. IEEE Robotics & Automation Magazine, 29(3):67–77, 2022. [bibtex] [pdf] [url] [doi]

Tamas Bates, Jens Kober, and Michael Gienger. Head-tracked off-axis perspective projection improves gaze readability of 3D virtual avatars. In SIGGRAPH Asia Technical Briefs, pp. 1–4, 2018. [bibtex] [pdf] [doi]