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CORDIS - Resultados de investigaciones de la UE
CORDIS

Reconstructing the Past: Artificial Intelligence and Robotics Meet Cultural Heritage

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

Integration guidelines and plan 3 (se abrirá en una nueva ventana)

Describes the 3rd version of the guidelines and plans needed for a successful integration of the different components of the RePAIR system.

Integration guidelines and plan 1 (se abrirá en una nueva ventana)

Describes the 1st version of the guidelines and plans needed for a successful integration of the different components of the RePAIR system.

Integration guidelines and plan 2 (se abrirá en una nueva ventana)

Describes the 2nd version of the guidelines and plans needed for a successful integration of the different components of the RePAIR system.

Setup of integration and sharing repository (se abrirá en una nueva ventana)

Describes the setup of the repositories to be created to facilitate interaction during the development phase

Fragment recognition and pose estimation (se abrirá en una nueva ventana)

Describes the work done in WP2.2 where we shall develop matching algorithms to recognise and estimate the pose of the fragments, given possibly partial views and different sensor modalities.

Bi-manual motion planning (se abrirá en una nueva ventana)

Describes the work done in WP5.2 whew we will develop efficient motion planning techniques for the bi-manual robotic system.

Acquisition and 3D modelling of fragments (se abrirá en una nueva ventana)

Describes the work done in WP21 which will focus on deriving an accurate 3D model for each archaeological fragment together with a mapped texture so as to obtain appearance and geometrybased descriptors that will be used by the puzzlesolving and grasping modules

Hand pose selection for grasp planning using vision sensors (se abrirá en una nueva ventana)

Describes the work done in WP51 which aims to learn by explorationimitation the parameters of the visual servoing controllers for softhands

Adaptable bi-manual manipulation platform (se abrirá en una nueva ventana)

Describes the work done in WP4.2 which focuses on the development and control of a dedicated twin robot arm to execute the manipulation tasks of the fresco pieces.

Quality Management plan (se abrirá en una nueva ventana)

Sets the quality standards to be pursued in the whole project

Exploitation plan (including IP provisions) (se abrirá en una nueva ventana)

Describes the exploitation plan of the project including IP provisions

Manipulation platform requirements (se abrirá en una nueva ventana)

Describes the work done in WP41 and outlines the desired specifications of the robot and vision systems based on the requirements of the manipulation tasks with the fresco pieces

Style priors and their formal description for appearance prediction (se abrirá en una nueva ventana)

Describes the work done in WP31 where highlevel knowledge of fresco styles will be formalised in ways that allow its integration into the puzzle solving algorithm

View selection for visual perception tasks (se abrirá en una nueva ventana)

Describes the work done in WP5.3 which will develop optimisation methods to select the arm pose that provides the most informative visual input for a successful grasp.

End-effectors modules (se abrirá en una nueva ventana)

Describes the work done in WP 4.3 where we will leverage on soft robotic principles together with under-actuation to develop soft and adaptive end-effectors.

Strategic communication and dissemination plan (se abrirá en una nueva ventana)

Describes the strategic communication and dissemination plan of the project

Data Management Plan (se abrirá en una nueva ventana)

It provides indications as to the management of data in relation to the H2020 Open Research Data Pilot Data Management Plan might be updated during the project implementation

Publicaciones

3DSGrasp: 3D Shape-Completion for Robotic Grasp (se abrirá en una nueva ventana)

Autores: Seyed S. Mohammadi, Nuno F. Duarte, Dimitrios Dimou, Yiming Wang, Matteo Taiana, Pietro Morerio, Atabak Dehban, Plinio Moreno, Alexandre Bernardino, Alessio Del Bue, José Santos-Victor
Publicado en: 2023 IEEE International Conference on Robotics and Automation (ICRA), 2024, Página(s) 3815-3822
Editor: IEEE
DOI: 10.1109/icra48891.2023.10160350

Learning Goal-Oriented Non-Prehensile Pushing in Cluttered Scenes (se abrirá en una nueva ventana)

Autores: Nils Dengler, David Großklaus, Maren Bennewitz
Publicado en: 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024, Página(s) 1116-1122
Editor: IEEE
DOI: 10.1109/iros47612.2022.9981873

Relaxation labeling meets GANs: Solving jigsaw puzzles with missing borders (se abrirá en una nueva ventana)

Autores: M. Khoroshiltseva, A. Traviglia, M. Pelillo and S. Vascon
Publicado en: Proceedings of the 21st International Conference on Image Analysis and Processing, 2022
Editor: Springer
DOI: 10.1007/978-3-031-06433-3_3

Multi-phase relaxation labeling for square jigsaw puzzle solving (se abrirá en una nueva ventana)

Autores: B. Vardi, M. Khoroshiltseva, A. Torcinovich, M. Pelillo, and O. Ben-Shahar
Publicado en: Proceedings of the 18th International Joint Conference on Computer Vision, Imaging, and Computer Graphics: Theory and Applications, 2023
Editor: SCITEPRESS
DOI: 10.5220/0011622800003417

GANzzle: Reframing jigsaw puzzle solving as a retrieval task using a generative mental image (se abrirá en una nueva ventana)

Autores: D. Talon, A. Del Bue, S. James
Publicado en: Proceedings of IEEE International Conference on Image Processing, 2022
Editor: IEEE
DOI: 10.1109/icip46576.2022.9897553

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