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Automated Urban Parking and Driving

Deliverables

Software specification and architecture for the decision making and navigation

This deliverable will provide the general architecture of the navigation stack. It will list all software components involved in the decision making and navigation processes, the interfaces between them as well as to components from other work packages. It will also provide approaches identified to be pursued in the project.

Software specification and architecture for scene understanding

In this report detailed input and outputs of scene understanding will be produced. Input will include the specific interfaces from other Work Packages. Outputs will define the format of the data produced to detect the current scene and predict the expected behavior of traffic occupants. Also the Interfaces between the individual modules involved into scene understanding will be provided.

Specification of the map frontend and storage concept

This deliverable consists of all software and hardware specifications related to the mapping frontend and the internal map storage concept as described in Task 5.1 and Task 5.3, as well as a concept on how data is to be exchanged between the vehicles and the mapping backend.

Development infrastructure

A report documenting access to running instances of both the project-internal development repository and the public open-access repository together with issue-tracking and wiki support.

First vehicle platform available

This deliverable will mark the completion of the hardware and low level software of the first vehicle platform. It will include a vehicle manual with photos of all relevant hardware elements. This will be accompanied by figures and short descriptions of basic features of the communication, acquisition and processing framework. It will further provide a dataset including data from all sensors and a report with figures of visualized raw data. Finally it will provide a video demonstrating drive by wire operation using a gamepad / keyboard.

First development and integration cycle of cloud infrastructure

This deliverable describes the cloud infrastructure framework after the first development and integration cycle. All components, including the initial hardware stack, the development and deployment toolchain, the communication framework and the bulk data storage service are functional and fulfill their basic purpose. All components deliver first implementation results.

Initial specification and design of on-board sensing

The deliverable provides a report on the detailed specification of the perception goals and of the sensorial model of the environment. It also describes the sensors selection and their optimal setup configuration for obtaining a robust and redundant perception solution for each individual perception task – in alignment with the system-wide specification of WP1.

Brochure, newsletter

A nicely laid out brochure at M16 to inform the public about the project and its main objectives and content. A knowledge management report will be provided to keep internal and external experts informed about new knowledge or patents created in the project.

Project Web-page

The website including a public document database will be operational from month 2 on. It will be updated continuously during the project.

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Publications

Semantic segmentation-based stereo reconstruction with statistically improved long range accuracy

Author(s): Vlad-Cristian Miclea, Sergiu Nedevschi
Published in: 2017 IEEE Intelligent Vehicles Symposium (IV), 2017, Page(s) 1795-1802
DOI: 10.1109/IVS.2017.7995967

Traffic scene segmentation based on boosting over multimodal low, intermediate and high order multi-range channel features

Author(s): Arthur D. Costea, Sergiu Nedevschi
Published in: 2017 IEEE Intelligent Vehicles Symposium (IV), 2017, Page(s) 74-81
DOI: 10.1109/IVS.2017.7995701

Semi-automatic image annotation of street scenes

Author(s): Andra Petrovai, Arthur D. Costea, Sergiu Nedevschi
Published in: 2017 IEEE Intelligent Vehicles Symposium (IV), 2017, Page(s) 448-455
DOI: 10.1109/IVS.2017.7995759

Fast Boosting Based Detection Using Scale Invariant Multimodal Multiresolution Filtered Features

Author(s): Arthur Daniel Costea, Robert Varga, Sergiu Nedevschi
Published in: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017, Page(s) 993-1002
DOI: 10.1109/CVPR.2017.112

Super-sensor for 360-degree environment perception: Point cloud segmentation using image features

Author(s): Robert Varga, Arthur Costea, Horatiu Florea, Ion Giosan, Sergiu Nedevschi
Published in: 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC), 2017, Page(s) 1-8
DOI: 10.1109/ITSC.2017.8317846

Online cross-calibration of camera and LIDAR

Author(s): Bianca-Cerasela-Zelia Blaga, Sergiu Nedevschi
Published in: 2017 13th IEEE International Conference on Intelligent Computer Communication and Processing (ICCP), 2017, Page(s) 295-301
DOI: 10.1109/ICCP.2017.8117020

Real-time object detection using a sparse 4-layer LIDAR

Author(s): Mircea Paul Muresan, Sergiu Nedevschi, Ion Giosan
Published in: 2017 13th IEEE International Conference on Intelligent Computer Communication and Processing (ICCP), 2017, Page(s) 317-322
DOI: 10.1109/ICCP.2017.8117023

An approach for segmenting 3D LiDAR data using multi-volume grid structures

Author(s): Selma Goga, Sergiu Nedevschi
Published in: 2017 13th IEEE International Conference on Intelligent Computer Communication and Processing (ICCP), 2017, Page(s) 309-315
DOI: 10.1109/ICCP.2017.8117022

Real-time Semantic Segmentation-based Depth Upsampling using Deep Learning

Author(s): V. Miclea and S. Nedevschi
Published in: 2018

Lessons learned from developing the Gödel Deep Learning library

Author(s): Robert Varga
Published in: 2017

Boosting over deep convolutional features for object detection

Author(s): Arthur Costea
Published in: 2017

Fusion Scheme for Semantic and Instance-level Segmentation

Author(s): A. Costea, A. Petrovai, S. Nedevschi
Published in: Deep vision workshop; 2018 IEEE Conference on Computer Vision and Pattern Recognition (CVPR 18), 2018

Deep learning-based approaches for stereo reconstruction

Author(s): Vlad Miclea
Published in: 2017

Deep learning for semantic image segmentation

Author(s): Andra Petrovai
Published in: 2017

Fusion Scheme for Semantic and Instance-level Segmentation

Author(s): A.D. Costea, A. Petrovai, S. Nedevschi
Published in: 2018 IEEE 21th International Conference on Intelligent Transportation Systems (ITSC 2018), 2018

Appearance-Based Landmark Selection for Efficient Long-Term Visual Localization

Author(s): Mathias Buerki, Igor Gilitschenski, Elena Stumm, Roland Siegwart, and Juan Nieto
Published in: International Conference on Intelligent Robots and Systems (IROS) 2016, 2016

Modular Sensor Fusion for Semantic Segmentation

Author(s): Hermann Blum, Abel Gawel, Roland Siegwart, Cesar Cadena
Published in: 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018, Page(s) 3670-3677
DOI: 10.1109/IROS.2018.8593786

OREOS: Oriented Recognition of 3D Point Clouds in Outdoor Scenarios

Author(s): Schaupp, Lukas; Bürki, Mathias; Cadena, Cesar; Dube, Renaud; Siegwart, Roland
Published in: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Issue 1, 2019
DOI: 10.13140/rg.2.2.10859.59685

VIZARD: Reliable Visual Localization for Autonomous Vehicles in Urban Outdoor Environments

Author(s): Mathias Burki, Lukas Schaupp, Marcin Dymczyk, Renaud Dube, Cesar Cadena, Roland Siegwart, Juan Nieto
Published in: 2019 IEEE Intelligent Vehicles Symposium (IV), 2019, Page(s) 1124-1130
DOI: 10.1109/IVS.2019.8814017

Design of an Autonomous Racecar: Perception, State Estimation and System Integration

Author(s): Miguel I. Valls, Hubertus F.C. Hendrikx, Victor J.F. Reijgwart, Fabio V. Meier, Inkyu Sa, Renaud Dube, Abel Gawel, Mathias Burki, Roland Siegwart
Published in: 2018 IEEE International Conference on Robotics and Automation (ICRA), 2018, Page(s) 2048-2055
DOI: 10.1109/ICRA.2018.8462829

Map Management for Efficient Long-Term Visual Localization in Outdoor Environments

Author(s): Bürki, Mathias; Dymczyk, Marcin; Gilitschenski, Igor; Cadena, Cesar; Siegwart, Roland; Nieto, Juan
Published in: IEEE Intelligent Vehicles Symposium, Issue 1, 2018

A Fast Ransac Based Approach for Computing the Orientation of Obstacles in Traffic Scenes

Author(s): Florin Oniga, Sergiu Nedevschi
Published in: 2018 IEEE 14th International Conference on Intelligent Computer Communication and Processing (ICCP), 2018, Page(s) 209-214
DOI: 10.1109/iccp.2018.8516642

Curb detection in urban traffic scenarios using LiDARs point cloud and semantically segmented color images

Author(s): Selma Evelyn Catalina Deac, Ion Giosan, Sergiu Nedevschi
Published in: 2019 IEEE Intelligent Transportation Systems Conference (ITSC), 2019, Page(s) 3433-3440
DOI: 10.1109/itsc.2019.8917020

Efficient Instance and Semantic Segmentation for Automated Driving

Author(s): Andra Petrovai, Sergiu Nedevschi
Published in: 2019 IEEE Intelligent Vehicles Symposium (IV), 2019, Page(s) 2575-2581
DOI: 10.1109/ivs.2019.8814177

Empty Cities: Image Inpainting for a Dynamic-Object-Invariant Space

Author(s): Berta Bescos, Jose Neira, Roland Siegwart, Cesar Cadena
Published in: 2019 International Conference on Robotics and Automation (ICRA), 2019, Page(s) 5460-5466
DOI: 10.1109/icra.2019.8794417

Environment Perception Architecture using Images and 3D Data

Author(s): Horatiu FLOREA, Robert VARGA, Sergiu NEDEVSCHI
Published in: 2018 IEEE 14th International Conference on Intelligent Computer Communication and Processing (ICCP), 2018, Page(s) 223-228
DOI: 10.1109/iccp.2018.8516581

Estimation of Absolute Scale in Monocular SLAM Using Synthetic Data

Author(s): Danila Rukhovich, Daniel Mouritzen, Ralf Kaestner, Martin Rufli, Alexander Velizhev
Published in: International Conference on Computer Vision (ICCV); Workshop on Computer Vision for Road Scene Understanding and Autonomous Driving, 2019

Semantic information based vehicle relative orientation and taillight detection

Author(s): Flaviu Ionut Vancea, Sergiu Nedevschi
Published in: 2018 IEEE 14th International Conference on Intelligent Computer Communication and Processing (ICCP), 2018, Page(s) 259-264
DOI: 10.1109/iccp.2018.8516631

Motion Prediction Influence on the Pedestrian Intention Estimation Near a Zebra Crossing

Author(s): J. Škovierová, A. Vobecký, M. Uller, R. Škoviera, V. Hlaváč
Published in: 4th International Conference on Vehicle Technology and Intelligent Transport Systems (VEHITS 2018), 2018

Multi-Object Tracking of 3D Cuboids Using Aggregated Features

Author(s): Mircea Paul Muresan, Sergiu Nedevschi
Published in: 2019 IEEE 15th International Conference on Intelligent Computer Communication and Processing (ICCP), 2019, Page(s) 11-18
DOI: 10.1109/iccp48234.2019.8959552

Multi-task Network for Panoptic Segmentation in Automated Driving

Author(s): Andra Petrovai, Sergiu Nedevschi
Published in: 2019 IEEE Intelligent Transportation Systems Conference (ITSC), 2019, Page(s) 2394-2401
DOI: 10.1109/itsc.2019.8917422

Object Classification Based on Unsupervised Learned Multi-Modal Features For Overcoming Sensor Failures

Author(s): Julia Nitsch, Juan Nieto, Roland Siegwart, Max Schmidt, Cesar Cadena
Published in: 2019 International Conference on Robotics and Automation (ICRA), 2019, Page(s) 4369-4375
DOI: 10.1109/icra.2019.8793628

Robust Maximum-likelihood On-line LiDAR-to-Camera Calibration Monitoring and Refinement

Author(s): J. Moravec, R. Šára
Published in: Proceedings of the 23rd Computer Vision Winter Workshop, 2018

Fusing semantic labeled camera images and 3D LiDAR data for the detection of urban curbs

Author(s): Selma Evelyn Catalina Goga, Sergiu Nedevschi
Published in: 2018 IEEE 14th International Conference on Intelligent Computer Communication and Processing (ICCP), 2018, Page(s) 301-308
DOI: 10.1109/iccp.2018.8516649

A Decentralized Trust-minimized Cloud Robotics Architecture

Author(s): Alessandro Simovic, Ralf Kaestner, Martin Rufli
Published in: 2017

Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age

Author(s): Cesar Cadena, Luca Carlone, Henry Carrillo, Yasir Latif, Davide Scaramuzza, Jose Neira, Ian Reid, John J. Leonard
Published in: IEEE Transactions on Robotics, Issue 32/6, 2016, Page(s) 1309-1332, ISSN 1552-3098
DOI: 10.1109/TRO.2016.2624754

Appearance‐based landmark selection for visual localization


Published in: ISSN 1556-4959
DOI: 10.1002/rob.21870

Maplab: An Open Framework for Research in Visual-Inertial Mapping and Localization

Author(s): Thomas Schneider, Marcin Dymczyk, Marius Fehr, Kevin Egger, Simon Lynen, Igor Gilitschenski, Roland Siegwart
Published in: IEEE Robotics and Automation Letters, Issue 3/3, 2018, Page(s) 1418-1425, ISSN 2377-3766
DOI: 10.1109/LRA.2018.2800113

Multiple Hypothesis Semantic Mapping for Robust Data Association

Author(s): Lukas Bernreiter, Abel Roman Gawel, Hannes Sommer, Juan Nieto, Roland Siegwart, Cesar Cadena Lerma
Published in: IEEE Robotics and Automation Letters, 2019, Page(s) 1-1, ISSN 2377-3766
DOI: 10.1109/lra.2019.2925756

Real-Time Semantic Segmentation-Based Stereo Reconstruction

Author(s): Vlad-Cristian Miclea, Sergiu Nedevschi
Published in: IEEE Transactions on Intelligent Transportation Systems, 2019, Page(s) 1-11, ISSN 1524-9050
DOI: 10.1109/tits.2019.2913883

SegMap: Segment-based mapping and localization using data-driven descriptors

Author(s): Renaud Dubé, Andrei Cramariuc, Daniel Dugas, Hannes Sommer, Marcin Dymczyk, Juan Nieto, Roland Siegwart, Cesar Cadena
Published in: The International Journal of Robotics Research, Issue 39/2-3, 2020, Page(s) 339-355, ISSN 0278-3649
DOI: 10.1177/0278364919863090

Stabilization and Validation of 3D Object Position Using Multimodal Sensor Fusion and Semantic Segmentation

Author(s): Mircea Paul Muresan, Ion Giosan, Sergiu Nedevschi
Published in: Sensors, Issue 20/4, 2020, Page(s) 1110, ISSN 1424-8220
DOI: 10.3390/s20041110