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Zhu, J. (author), Gienger, Michael (author), Franzese, G. (author), Kober, J. (author)
Developing physically assistive robots capable of dressing assistance has the potential to significantly improve the lives of the elderly and disabled population. However, most robotics dressing strategies considered a single robot only, which greatly limited the performance of the dressing assistance. In fact, healthcare professionals...
journal article 2024
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Pérez-Dattari, Rodrigo (author), Kober, J. (author)
Learning from humans allows nonexperts to program robots with ease, lowering the resources required to build complex robotic solutions. Nevertheless, such data-driven approaches often lack the ability to provide guarantees regarding their learned behaviors, which is critical for avoiding failures and/or accidents. In this work, we focus on...
journal article 2023
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Ding, J. (author), Sels, Mees A.van Loben (author), Angelini, Franco (author), Kober, J. (author), Della Santina, C. (author)
Quadrupeds deployed in real-world scenarios need to be robust to unmodelled dynamic effects. In this work, we aim to increase the robustness of quadrupedal periodic forward jumping (i.e., pronking) by unifying cutting-edge model-based trajectory optimization and iterative learning control. Using a reduced-order soft anchor model, the...
journal article 2023
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Zhu, J. (author), Cherubini, Andrea (author), Dune, Claire (author), Navarro-Alarcon, David (author), Alambeigi, Farshid (author), Berenson, Dmitry (author), Ficuciello, Fanny (author), Harada, Kensuke (author), Kober, J. (author), Yuan, Wenzhen (author)
Deformable object manipulation (DOM) is an emerging research problem in robotics. The ability to manipulate deformable objects endows robots with higher autonomy and promises new applications in the industrial, services, and health-care sectors. However, compared to rigid object manipulation, the manipulation of deformable objects is...
journal article 2022
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Mészáros, A. (author), Franzese, G. (author), Kober, J. (author)
This work investigates how the intricate task of a continuous pick & place (P&P) motion may be learned from humans based on demonstrations and corrections. Due to the complexity of the task, these demonstrations are often slow and even slightly flawed, particularly at moments when multiple aspects (i.e., end-effector movement,...
journal article 2022
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