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UP-Drive SIGNED

Automated Urban Parking and Driving

Total Cost €

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EC-Contrib. €

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Partnership

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Project "UP-Drive" data sheet

The following table provides information about the project.

Coordinator
VOLKSWAGEN AG 

Organization address
address: BERLINER RING 2
city: WOLFSBURG
postcode: 38440
website: www.volkswagen.de

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Germany [DE]
 Project website http://up-drive.eu/
 Total cost 7˙604˙893 €
 EC max contribution 4˙671˙896 € (61%)
 Programme 1. H2020-EU.2.1.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT))
 Code Call H2020-ICT-2015
 Funding Scheme RIA
 Starting year 2016
 Duration (year-month-day) from 2016-01-01   to  2019-12-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    VOLKSWAGEN AG DE (WOLFSBURG) coordinator 3˙020˙487.00
2    UNIVERSITATEA TEHNICA CLUJ-NAPOCA RO (CLUJ NAPOCA) participant 897˙708.00
3    CESKE VYSOKE UCENI TECHNICKE V PRAZE CZ (PRAHA) participant 753˙700.00
4    EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH CH (ZUERICH) participant 0.00
5    IBM RESEARCH GMBH CH (RUESCHLIKON) participant 0.00

Map

 Project objective

Automation of individual transport systems is considered an up-and-coming prospect with the potential of greatly mitigating many of the challenges associated with intensified urbanization, while at the same time offering additional benefits for the citizens and drastically increasing overall street safety. However, due to the lack of maturity of involved key technologies and persisting legal limitations, full automation of on-road driving remains a longer-term vision, particularly in urban environments.

The goal and ambition of UP-Drive is to address these technological challenges through the development of an automated valet parking service for city environments, aimed at relieving a car driver from the burden of finding a parking space in city centers. Instead, the fully automated car navigates on its own through urban neighborhoods, finds a parking space and returns on-demand.

Creating such a system requires mastering all key technologies essential to automated urban driving beyond the current state-of-the-art: complete round-view perception of the vehicle environment, robust lifelong localization and mapping, sophisticated understanding of complex scenes as well as aggregation and integration of long-term semantic data over a cloud-based infrastructure. With this, we ensure that the research and development carried out in this project will directly be applicable to other urban driving use-cases such as driver assistance and safety systems on the one hand, and on the other hand to the transportation for elderly and citizens with handicaps, last-mile delivery of goods - and ultimately fully automated urban driving in general.

The consortium will continuously integrate the research and development from all partners into a fully functional vehicle platform and will showcase the end-product in its full extent to the general public.

 Deliverables

List of deliverables.
First development and integration cycle of cloud infrastructure Documents, reports 2019-05-30 14:23:06
Brochure, newsletter Websites, patent fillings, videos etc. 2019-05-30 14:22:54
Project Web-page Websites, patent fillings, videos etc. 2019-05-30 14:22:53
Software specification and architecture for the decision making and navigation Documents, reports 2019-05-30 14:22:51
Software specification and architecture for scene understanding Documents, reports 2019-05-30 14:22:53
Specification of the map frontend and storage concept Documents, reports 2019-05-30 14:22:50
First vehicle platform available Documents, reports 2019-05-30 14:23:04
Initial specification and design of on-board sensing Documents, reports 2019-05-30 14:22:50
Development infrastructure Documents, reports 2019-05-30 14:23:07

Take a look to the deliverables list in detail:  detailed list of UP-Drive deliverables.

 Publications

year authors and title journal last update
List of publications.
2016 Michal Uřičář, Vojtěch Franc, Diego Thomas, Akihiro Sugimoto, Václav Hlaváč
Multi-view facial landmark detector learned by the Structured Output SVM
published pages: 45-59, ISSN: 0262-8856, DOI: 10.1016/j.imavis.2016.02.004
Image and Vision Computing 47 2020-03-24
2020 Mircea Paul Muresan, Ion Giosan, Sergiu Nedevschi
Stabilization and Validation of 3D Object Position Using Multimodal Sensor Fusion and Semantic Segmentation
published pages: 1110, ISSN: 1424-8220, DOI: 10.3390/s20041110
Sensors 20/4 2020-03-24
2020 Renaud Dubé, Andrei Cramariuc, Daniel Dugas, Hannes Sommer, Marcin Dymczyk, Juan Nieto, Roland Siegwart, Cesar Cadena
SegMap: Segment-based mapping and localization using data-driven descriptors
published pages: 339-355, ISSN: 0278-3649, DOI: 10.1177/0278364919863090
The International Journal of Robotics Research 39/2-3 2020-03-24
2019 Mathias Bürki, Cesar Cadena, Igor Gilitschenski, Roland Siegwart, Juan Nieto
Appearance‐based landmark selection for visual localization
published pages: 1041-1073, ISSN: 1556-4959, DOI: 10.1002/rob.21870
Journal of Field Robotics 36/6 2020-03-24
2017 Vladimír Petrík, Vladimír Smutný, Pavel Krsek, Václav Hlaváč
Single arm robotic garment folding path generation
published pages: 1325-1337, ISSN: 0169-1864, DOI: 10.1080/01691864.2017.1367325
Advanced Robotics 31/23-24 2020-03-24
2018 Thomas Schneider, Marcin Dymczyk, Marius Fehr, Kevin Egger, Simon Lynen, Igor Gilitschenski, Roland Siegwart
Maplab: An Open Framework for Research in Visual-Inertial Mapping and Localization
published pages: 1418-1425, ISSN: 2377-3766, DOI: 10.1109/LRA.2018.2800113
IEEE Robotics and Automation Letters 3/3 2020-03-24
2019 Schaupp, Lukas; Bürki, Mathias; Cadena, Cesar; Dube, Renaud; Siegwart, Roland
OREOS: Oriented Recognition of 3D Point Clouds in Outdoor Scenarios
published pages: , ISSN: , DOI: 10.13140/rg.2.2.10859.59685
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 1 2020-03-24
2016 Kostiantyn Antoniuk, Vojtěch Franc, Václav Hlaváč
V-shaped interval insensitive loss for ordinal classification
published pages: 261-283, ISSN: 0885-6125, DOI: 10.1007/s10994-015-5541-9
Machine Learning 103/2 2020-03-24
2019 Vlad-Cristian Miclea, Sergiu Nedevschi
Real-Time Semantic Segmentation-Based Stereo Reconstruction
published pages: 1-11, ISSN: 1524-9050, DOI: 10.1109/tits.2019.2913883
IEEE Transactions on Intelligent Transportation Systems 2020-03-24
2018 J. Škovierová, A. Vobecký, M. Uller, R. Škoviera, V. Hlaváč
Motion Prediction Influence on the Pedestrian Intention Estimation Near a Zebra Crossing
published pages: , ISSN: , DOI:
4th International Conference on Vehicle Technology and Intelligent Transport Systems (VEHITS 2018) 2020-03-24
2019 Danila Rukhovich, Daniel Mouritzen, Ralf Kaestner, Martin Rufli, Alexander Velizhev
Estimation of Absolute Scale in Monocular SLAM Using Synthetic Data
published pages: , ISSN: , DOI:
International Conference on Computer Vision (ICCV); Workshop on Computer Vision for Road Scene Understanding and Autonomous Driving 2020-03-24
2019 Lukas Bernreiter, Abel Roman Gawel, Hannes Sommer, Juan Nieto, Roland Siegwart, Cesar Cadena Lerma
Multiple Hypothesis Semantic Mapping for Robust Data Association
published pages: 1-1, ISSN: 2377-3766, DOI: 10.1109/lra.2019.2925756
IEEE Robotics and Automation Letters 2020-03-24
2018 Bürki, Mathias; Dymczyk, Marcin; Gilitschenski, Igor; Cadena, Cesar; Siegwart, Roland; Nieto, Juan
Map Management for Efficient Long-Term Visual Localization in Outdoor Environments
published pages: , ISSN: , DOI:
IEEE Intelligent Vehicles Symposium 1 2020-03-24
2018 J. Moravec, R. Šára
Robust Maximum-likelihood On-line LiDAR-to-Camera Calibration Monitoring and Refinement
published pages: , ISSN: , DOI:
Proceedings of the 23rd Computer Vision Winter Workshop 2020-03-24
2017 Vlad Miclea
Deep learning-based approaches for stereo reconstruction
published pages: , ISSN: , DOI:
2019-06-18
2017 Robert Varga
Lessons learned from developing the Gödel Deep Learning library
published pages: , ISSN: , DOI:
2019-06-18
2017 Alessandro Simovic, Ralf Kaestner, Martin Rufli
A Decentralized Trust-minimized Cloud Robotics Architecture
published pages: , ISSN: , DOI:
2019-06-18
2017 Arthur Costea
Boosting over deep convolutional features for object detection
published pages: , ISSN: , DOI:
2019-06-18
2018 V. Miclea and S. Nedevschi
Real-time Semantic Segmentation-based Depth Upsampling using Deep Learning
published pages: , ISSN: , DOI:
2019-06-18
2018 A. Costea, A. Petrovai, S. Nedevschi
Fusion Scheme for Semantic and Instance-level Segmentation
published pages: , ISSN: , DOI:
2019-06-18
2017 Andra Petrovai
Deep learning for semantic image segmentation
published pages: , ISSN: , DOI:
2019-06-18
2017 A.D. Costea, A. Petrovai, S. Nedevschi
Fusion Scheme for Semantic and Instance-level Segmentation
published pages: , ISSN: , DOI:
2019-06-18
2016 Cesar Cadena, Luca Carlone, Henry Carrillo, Yasir Latif, Davide Scaramuzza, Jose Neira, Ian Reid, John J. Leonard
Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age
published pages: 1309-1332, ISSN: 1552-3098, DOI: 10.1109/TRO.2016.2624754
IEEE Transactions on Robotics 32/6 2019-06-18
2016 Mathias Buerki, Igor Gilitschenski, Elena Stumm, Roland Siegwart, and Juan Nieto
Appearance-Based Landmark Selection for Efficient Long-Term Visual Localization
published pages: , ISSN: , DOI:
International Conference on Intelligent Robots and Systems (IROS) 2016 2019-06-18

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The information about "UP-DRIVE" are provided by the European Opendata Portal: CORDIS opendata.

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