28 citations · 49 across the 5 of their papers we have counts for
5 papers
Fine-tuning Myoelectric Control through Reinforcement Learning in a Game Environment
Kilian Freitag, Yiannis Karayiannidis, Jan Zbinden +1
Objective: Enhancing the reliability of myoelectric controllers that decode motor intent is a pressing challenge in the field of bionic prosthetics. State-of-the-art research has m…
Curriculum Reinforcement Learning for Complex Reward Functions
Kilian Freitag, Kristian Ceder, Rita Laezza +2
Reinforcement learning (RL) has emerged as a powerful tool for tackling control problems, but its practical application is often hindered by the complexity arising from intricate r…
Offline Goal-Conditioned Reinforcement Learning for Shape Control of Deformable Linear Objects
Rita Laezza, Mohammadreza Shetab-Bushehri, Gabriel Arslan Waltersson +3
Deformable objects present several challenges to the field of robotic manipulation. One of the tasks that best encapsulates the difficulties arising due to non-rigid behavior is sh…
Feel the Tension: Manipulation of Deformable Linear Objects in Environments with Fixtures using Force Information
Finn Süberkrüb, Rita Laezza, Yiannis Karayiannidis
Humans are able to manipulate Deformable Linear Objects (DLOs) such as cables and wires, with little or no visual information, relying mostly on force sensing. In this work, we pro…
Learning Shape Control of Elastoplastic Deformable Linear Objects
Rita Laezza, Yiannis Karayiannidis
Deformable object manipulation tasks have long been regarded as challenging robotic problems. However, until recently very little work has been done on the subject, with most robot…