Titlebook: Human-Friendly Robotics 2022; HFR: 15th Internatio Pablo Borja,Cosimo Della Santina,Elena Torta Conference proceedings 2023 The Editor(s) (

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,Simulative and Experimental Evaluation of a Soft-DTW Neural Network for sEMG-Based Robotic Graspingerformance with desynchronized labelling, whereas an online experiment was carried out to control both a simulated and a real robotic hand. The obtained results demonstrate that the presented method allows minimally supervised regression of sEMG signals, reporting performances comparable with standa

reaching

,Toward Human-Robot Cooperation: Unsupervised Domain Adaptation for Egocentric Action Recognition,rform Domain Adaptation with no external supervision, which we test on the EPIC-Kitchens-100 UDA Challenge in Action Recognition. More specifically, we move from our previous work on Relative Norm Alignment and extend the approach to unlabelled target data, enabling a simpler adaptation of the model

CHYME

Use of EEG Signals for Mental Workload Assessment in Human-Robot Collaboration,ans of a BITalino (R)Evolution Board in order to compare the results obtained from the two biosignals and evaluate the indices deriving from the spectral powers of the rhythms. Most of the workload indices, present in the literature, used for the analysis of this work have proved, on the basis of th

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hieroglyphic

Thyroid-Gland

Friction

Approximating Robot Reachable Space Using Convex Polytopes,s the reachable space over a given time horizon based on the robot’s actuation limits and kinematic constraints. The approach is furthermore extended to integrate the robot’s environment, assuming it can be expressed in a form of linear constraints, and to account for the robot’s link geometry. The

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exceptional

,Damping Design for Robot Manipulators,ing matrix—alternatively, the derivative gain of a PD controller—of the closed-loop system such that . second-order systems can approximate its behavior with a prescribed damping coefficient, where . denotes the degrees of freedom of the system. The proposed approach is based on the linearization of

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,Deformation-Aware Contact-Rich Manipulation Skills Learning and Compliant Control,m demonstration. For contact-rich tasks, the compliant control method is essential, especially when interacting with a deformable object with unknown properties, such as pizza dough. Learning from demonstration (LfD) provides a solution for this challenging task. However, the generalisation capabili