iMmersive leArninG for ImperfeCtion detectIon and repAir through human-robot interactioN

Información del proyecto

MAGICIAN

Identificador del acuerdo de subvención: 101120731

DOI

10.3030/101120731

Fecha de la firma de la CE 30 Junio 2023

Fecha de inicio 1 Octubre 2023

Fecha de finalización 30 Septiembre 2027

Financiado con arreglo a

• Digital, Industry and Space

Coste total

€ 9 174 031,25

Aportación de la UE

€ 8 332 681,25

Coordinado por

UNIVERSITA DEGLI STUDI DI TRENTO
Italy

CORDIS proporciona enlaces a los documentos públicos y las publicaciones de los proyectos de los programas marco HORIZONTE.

Los enlaces a los documentos y las publicaciones de los proyectos del Séptimo Programa Marco, así como los enlaces a algunos tipos de resultados específicos, como conjuntos de datos y «software», se obtienen dinámicamente de OpenAIRE .

Resultado final

Documents, reports (2)

Initial user requirements report

Definition of the user requirements for the first use case

First coordination report

Periodic report on the project work progress and activities performed

Other (2)

Human-Robot interfaces and intelligence

First release of the algorithms for planning, active sensing and control of the robot activities

First delivery of perception systems

Preliminary version of target analysis and dataset acquisition and annotation, visual perception module for imperfections detection, tactile sensing system and human motion detection and tracking

Publicaciones

Peer reviewed articles (3)

Force-Based Viscosity and Elasticity Measurements for Material Biomechanical Characterization With a Collaborative Robotic Arm

Autores: Luca Beber, Edoardo Lamon, Giacomo Moretti, Matteo Saveriano, Luca Fambri, Luigi Palopoli, Daniele Fontanelli
Publicado en: IEEE Transactions on Instrumentation and Measurement, Edición 74, 2025, ISSN 0018-9456
Editor: Institute of Electrical and Electronics Engineers (IEEE)
DOI: 10.1109/TIM.2025.3581663

Surface defect identification using Bayesian filtering on a 3D mesh

Autores: Matteo Dalle Vedove, Matteo Bonetto, Edoardo Lamon, Luigi Palopoli, Matteo Saveriano, Daniele Fontanelli
Publicado en: Measurement: Sensors, 2025, ISSN 2665-9174
Editor: Elsevier BV
DOI: 10.1016/J.MEASEN.2025.101849

Towards an experiential ethics of AI and robots: A review of empirical research on human encounters

Autores: Björn Fischer, Susanne Frennert
Publicado en: Technological Forecasting and Social Change, Edición 219, 2025, ISSN 0040-1625
Editor: Elsevier BV
DOI: 10.1016/J.TECHFORE.2025.124264

Conference proceedings (5)

Leveraging FINCH and K-means for Enhanced Cluster-Based Instance Selection

Autores: Zotou, Panagiota; Bacharidis, Konstantinos; Argyros, Antonis
Publicado en: 18th European Conference on Computer Vision, ECCV 2024, 2024
Editor: ECCV
DOI: 10.5281/ZENODO.14591725

A Passivity-Based Variable Impedance Controller for Incremental Learning of Periodic Interactive Tasks

Autores: Matteo Dalle Vedove, Edoardo Lamon, Daniele Fontanelli, Luigi Palopoli, Matteo Saveriano
Publicado en: 2024 IEEE 20th International Conference on Automation Science and Engineering (CASE), 2024
Editor: IEEE
DOI: 10.1109/CASE59546.2024.10711399

Conditional Hand Image Generation using Latent Space Supervision in Random Variable Variational Autoencoders

Autores: Nicodemou, Vassilios - Clitos; Oikonomidis, Iason; KARVOUNAS, GIORGOS; Argyros, Antonis
Publicado en: 18th European Conference on Computer Vision, ECCV 2024, 2024
Editor: EVVC
DOI: 10.5281/ZENODO.14591955

Learning Priors of Human Motion With Vision Transformers

Autores: Placido Falqueto, Alberto Sanfeliu, Luigi Palopoli, Daniele Fontanelli
Publicado en: 2024 IEEE 48th Annual Computers, Software, and Applications Conference (COMPSAC), 2024
Editor: IEEE
DOI: 10.48550/ARXIV.2501.18543

MeshDMP: Motion Planning on Discrete Manifolds using Dynamic Movement Primitives

Autores: Matteo Dalle Vedove, Fares J. Abu-Dakka, Luigi Palopoli, Daniele Fontanelli, Matteo Saveriano
Publicado en: 2025 IEEE International Conference on Robotics and Automation, 2025
Editor: IEEE
DOI: 10.48550/ARXIV.2410.15123