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CORDIS - Forschungsergebnisse der EU
CORDIS

Reconstructing the Past: Artificial Intelligence and Robotics Meet Cultural Heritage

CORDIS bietet Links zu öffentlichen Ergebnissen und Veröffentlichungen von HORIZONT-Projekten.

Links zu Ergebnissen und Veröffentlichungen von RP7-Projekten sowie Links zu einigen Typen spezifischer Ergebnisse wie Datensätzen und Software werden dynamisch von OpenAIRE abgerufen.

Leistungen

Integration guidelines and plan 3 (öffnet in neuem Fenster)

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 (öffnet in neuem Fenster)

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 (öffnet in neuem Fenster)

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 (öffnet in neuem Fenster)

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

Fragment recognition and pose estimation (öffnet in neuem Fenster)

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 (öffnet in neuem Fenster)

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 (öffnet in neuem Fenster)

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 (öffnet in neuem Fenster)

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 (öffnet in neuem Fenster)

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 (öffnet in neuem Fenster)

Sets the quality standards to be pursued in the whole project

Exploitation plan (including IP provisions) (öffnet in neuem Fenster)

Describes the exploitation plan of the project including IP provisions

Manipulation platform requirements (öffnet in neuem Fenster)

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 (öffnet in neuem Fenster)

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 (öffnet in neuem Fenster)

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 (öffnet in neuem Fenster)

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 (öffnet in neuem Fenster)

Describes the strategic communication and dissemination plan of the project

Data Management Plan (öffnet in neuem Fenster)

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

Veröffentlichungen

3DSGrasp: 3D Shape-Completion for Robotic Grasp (öffnet in neuem Fenster)

Autoren: 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
Veröffentlicht in: 2023 IEEE International Conference on Robotics and Automation (ICRA), 2024, Seite(n) 3815-3822
Herausgeber: IEEE
DOI: 10.1109/icra48891.2023.10160350

Learning Goal-Oriented Non-Prehensile Pushing in Cluttered Scenes (öffnet in neuem Fenster)

Autoren: Nils Dengler, David Großklaus, Maren Bennewitz
Veröffentlicht in: 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024, Seite(n) 1116-1122
Herausgeber: IEEE
DOI: 10.1109/iros47612.2022.9981873

Relaxation labeling meets GANs: Solving jigsaw puzzles with missing borders (öffnet in neuem Fenster)

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

Multi-phase relaxation labeling for square jigsaw puzzle solving (öffnet in neuem Fenster)

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

GANzzle: Reframing jigsaw puzzle solving as a retrieval task using a generative mental image (öffnet in neuem Fenster)

Autoren: D. Talon, A. Del Bue, S. James
Veröffentlicht in: Proceedings of IEEE International Conference on Image Processing, 2022
Herausgeber: IEEE
DOI: 10.1109/icip46576.2022.9897553

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