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CORDIS

Safety Enables Cooperation in Uncertain Robotic Environments

Fact Sheet

Reporting

Results

Objective

The majority of existing robots in industry are pre-programmed robots working in safety zones, with visual or auditory warning signals and little concept of intelligent safety awareness necessary for dynamic and unpredictable human or domestic environments. In the future, novel cognitive robotic companions will be developed, ranging from service robots to humanoid robots, which should be able to learn from users and adapt to open dynamic contexts. The development of such robot companions will lead to new challenges for human-robot cooperation and safety, going well beyond the current state of the art. Therefore, the SECURE project aims to train a new generation of researchers on safe cognitive robot concepts for human work and living spaces on the most advanced humanoid robot platforms available in Europe. The fellows will be trained through an innovative concept of project-based learning and constructivist learning in supervised peer networks where they will gain experience from an intersectoral programme involving universities, research institutes, large and SME companies from public and private sectors. The training domain will integrate multidisciplinary concepts from the fields of cognitive human-robot interaction, computer science and intelligent robotics where a new approach of integrating principles of embodiment, situation and interaction will be pursued to address future challenges for safe human-robot environments.

Programme(s)

H2020-EU.1.3.1. - Fostering new skills by means of excellent initial training of researchers

Topic(s)

MSCA-ITN-2014-ETN - Marie Skłodowska-Curie Innovative Training Networks (ITN-ETN)

Call for proposal

H2020-MSCA-ITN-2014

See other projects for this call

Funding Scheme

MSCA-ITN-ETN - European Training Networks

Leaflet | Map data © OpenStreetMap contributors, Credit: EC-GISCO, © EuroGeographics for the administrative boundaries

Coordinator

UNIVERSITAET HAMBURG

Address

Mittelweg 177
20148 Hamburg

Germany

Activity type

Higher or Secondary Education Establishments

EU Contribution

€ 740 726,76

Contact the organisation

Participants (6)

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UNIVERSITY OF PLYMOUTH

United Kingdom

EU Contribution

€ 447 888,47

FONDAZIONE ISTITUTO ITALIANO DI TECNOLOGIA

Italy

EU Contribution

€ 516 122,64

THE UNIVERSITY OF HERTFORDSHIRE HIGHER EDUCATION CORPORATION

United Kingdom

EU Contribution

€ 546 575,76

FRAUNHOFER GESELLSCHAFT ZUR FOERDERUNG DER ANGEWANDTEN FORSCHUNG E.V.

Germany

EU Contribution

€ 498 432,96

DANIELI TELEROBOT LABS S.R.L.

Italy

EU Contribution

€ 258 061,32

THE UNIVERSITY OF MANCHESTER

United Kingdom

EU Contribution

€ 98 687,29

Project information

SECURE

Grant agreement ID: 642667

Project website

Status

Closed project

Start date

1 September 2015
End date

31 August 2019

Funded under:

H2020-EU.1.3.1.

Overall budget:

€ 3 106 495,20
EU contribution

€ 3 106 495,20

Coordinated by:

UNIVERSITAET HAMBURG

Germany

Periodic Reporting for period 1 - SECURE (Safety Enables Cooperation in Uncertain Robotic Environments)

Reporting period: 2015-09-01 to 2017-08-31

Summary of the context and overall objectives of the project

The majority of existing robots in industry are pre-programmed robots working in safety zones, with visual or auditory warning signals and little concept of intelligent safety awareness necessary for dynamic and unpredictable domestic environments. In the future, novel cognitive robotic companions will be developed, which should be able to learn from users and adapt to open dynamic contexts. The development of such robot companions will lead to new challenges for human-robot cooperation and safety, going well beyond the current state of the art. Therefore, the SECURE project aims to train a new generation of researchers on safe cognitive robot concepts for human work and living spaces on the most advanced humanoid robot platforms available in Europe. The aim is clearly reflected in the main objectives of the SECURE project: To teach PhD researchers on issues surrounding safety in cognitive robotic companions for domestic use and to enhance the fellows’ expertise on the multidisciplinary aspects of human-robot interaction (HRI), cognition, computer science, robotics and on transferable skills for research and development. To account for the highly interdisciplinary nature of this endeavour, the scientific work is separated into three competence areas that represent three research areas in human-robot interaction: “Embodiment”, “Situation”, and “Interaction”.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

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Project information

SECURE

Grant agreement ID: 642667

Project website

Status

Closed project

Start date

1 September 2015
End date

31 August 2019

Funded under:

H2020-EU.1.3.1.

Overall budget:

€ 3 106 495,20
EU contribution

€ 3 106 495,20

Coordinated by:

UNIVERSITAET HAMBURG

Deliverables

Documents, reports (6)

Proceedings of SECURE PhD Conference

Proceedings of Int. SECURE Conference

Press releases to media

Training material for network-wide training

Progress Report

state of play project

Mid Term review meeting

state of play project

Other (2)

Training events

Scientific publications

Websites, patent fillings, videos etc. (1)

Publications

Conference proceedings (14)

Conversational Analysis Using Utterance-level Attention-based Bidirectional Recurrent Neural Networks

Author(s): Chandrakant Bothe, Sven Magg, Cornelius Weber, Stefan Wermter

Published in: Interspeech 2018, 2018, Page(s) 996-1000

DOI: 10.21437/interspeech.2018-2527

Learning Spatial Representation for Secure Human-Robot Collaboration in Joint Manual Tasks

Author(s): Zamani, M.A., Beik-Mohammadi, H., Kerzel, M., Magg, S., Wermter, S

Published in: Proceedings of ICRA workshop on the WORKplace is better with intelligent, collaborative, robot MATEs (WORKMATE), 2018

Sample-efficient deep reinforcement learning with imaginary rollouts for human-robot interaction

Author(s): Mohammad Thabet, Angelo Cangelosi

Published in: 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2019

MoonGrad at SemEval-2019 Task 3: Ensemble BiRNNs for Contextual Emotion Detection in Dialogues

Author(s): Chandrakant Bothe, Stefan Wermter

Published in: Proceedings of the 13th International Workshop on Semantic Evaluation, 2019, Page(s) 261-265

DOI: 10.18653/v1/s19-2044

Evaluation of an Industrial Robotic Assistant in an Ecological Environment

Author(s): Busch, Baptiste ; Cotugno, Giuseppe ; Khoramshahi, Mahdi ; Skaltsas, Grigorios ; Turchi, Dario ; Urbano, Leonardo ; Wächter, Mirko ; Zhou, You ; Asfour, Tamim ; Deacon, Graham ; Russel, Duncan ; Billard, Aude

Published in: Proceedings of the IEEE RoMan Converence 2019, 2019

On-line joint limit avoidance for torque controlled robots by joint space parametrization

Author(s): Charbonneau, M., Nori, F., Pucci, D.

Published in: 2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids), 2016, Page(s) 899-904

DOI: 10.1109/HUMANOIDS.2016.7803379

Deep Reinforcement Learning using Symbolic Representation for Performing Spoken Language Instructions.

Author(s): Zamani, M.A., Magg, S., Weber, C., and Wermter, S.

Published in: In 2nd Workshop on Behavior Adaptation, Interaction and Learning for Assistive Robotics (BAILAR) in the 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN)., 2017

KT-Speech-Crawler: Automatic Dataset Construction for Speech Recognition from YouTube Videos

Author(s): Egor Lakomkin, Sven Magg, Cornelius Weber, Stefan Wermter

Published in: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, 2018, Page(s) 90-95

DOI: 10.18653/v1/d18-2016

Dialogue-based neural learning to estimate sentiment of next upcoming utterance

Author(s): Bothe, C., Magg, S., Weber, C., Wermter, S.

Published in: Artificial Neural Networks and Machine Learning – ICANN 2017, Issue LNCS vol. 10614, 2017, Page(s) 477-486

Investigating Human Perceptions of Trust in Robots for Safe HRI in Home Environments

Author(s): Rossi, A., Dautenhahn, K., Koay, K. L., & Saunders, J.

Published in: Proceedings of the Companion of the 2017 ACM/IEEE International Conference on Human-Robot Interaction, 2017, Page(s) 375-376

DOI: 10.1145/3029798.3034822

Reusing speech representations for auditory emotion recognition

Author(s): Lakomkin, E., Magg, S., Weber, C., Wermter, S.

Published in: Artificial Neural Networks and Machine Learning – ICANN 2017, Issue LNCS vol. 10614, 2017

Automatically augmenting an emotion dataset improves classification using audio

Author(s): Lakomkin, E., Weber, C., Wermter, S.

Published in: 15th Conference of the European Chapter of the Association for Computational Linguistics (EACL)., 2017

GradAscent at EmoInt-2017: Character- and Word-Level Recurrent Neural Network Models for Tweet Emotion Intensity Detection

Author(s): Lakomkin, E., Bothe, C., Wermter, S.

Published in: Proceedings of the 8th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, 2017

Neural End-to-End Learning of Reach for Grasp Ability with a 6-DoF Robot Arm

Author(s): Hadi Beik-Mohammadi, Matthias Kerzel, Michael Görner, Mohammad Ali Zamani, Manfred Eppe, Stefan Wermter

Published in: Proceedings of IROS 2018 Workshop on Machine Learning in Robot Motion Planning, 2018

Peer reviewed articles (5)

The impact of peoples’ personal dispositions and personalities on their trust of robots in an emergency scenario

Author(s): Alessandra Rossi, Kerstin Dautenhahn, Kheng Lee Koay, Michael L. Walters

Published in: Paladyn, Journal of Behavioral Robotics, Issue 9/1, 2018, Page(s) 137-154, ISSN 2081-4836

DOI: 10.1515/pjbr-2018-0010

iCub-HRI: A Software Framework for Complex Human–Robot Interaction Scenarios on the iCub Humanoid Robot

Author(s): Tobias Fischer, Jordi-Ysard Puigbò, Daniel Camilleri, Phuong D. H. Nguyen, Clément Moulin-Frier, Stéphane Lallée, Giorgio Metta, Tony J. Prescott, Yiannis Demiris, Paul F. M. J. Verschure

Published in: Frontiers in Robotics and AI, Issue 5, 2018, ISSN 2296-9144

DOI: 10.3389/frobt.2018.00022

Deep reinforcement learning using compositional representations for performing instructions

Author(s): Mohammad Ali Zamani, Sven Magg, Cornelius Weber, Stefan Wermter, Di Fu

Published in: Paladyn, Journal of Behavioral Robotics, Issue 9/1, 2018, Page(s) 358-373, ISSN 2081-4836

DOI: 10.1515/pjbr-2018-0026

DAC-h3: A Proactive Robot Cognitive Architecture to Acquire and Express Knowledge About the World and the Self

Author(s): Clement Moulin-Frier, Tobias Fischer, Maxime Petit, Gregoire Pointeau, Jordi-Ysard Puigbo, Ugo Pattacini, Sock Ching Low, Daniel Camilleri, Phuong Nguyen, Matej Hoffmann, Hyung Jin Chang, Martina Zambelli, Anne-Laure Mealier, Andreas Damianou, Giorgio Metta, Tony J. Prescott, Yiannis Demiris, Peter Ford Dominey, Paul F. M. J. Verschure

Published in: IEEE Transactions on Cognitive and Developmental Systems, Issue 10/4, 2018, Page(s) 1005-1022, ISSN 2379-8920

DOI: 10.1109/TCDS.2017.2754143

Adaptable Workstations for Human-Robot Collaboration: A Reconfigurable Framework for Improving Worker Ergonomics and Productivity

Author(s): Wansoo Kim, Marta Lorenzini, Pietro Balatti, Phuong D.H. Nguyen, Ugo Pattacini, Vadim Tikhanoff, Luka Peternel, Claudio Fantacci, Lorenzo Natale, Giorgio Metta, Arash Ajoudani

Published in: IEEE Robotics & Automation Magazine, Issue 26/3, 2019, Page(s) 14-26, ISSN 1070-9932

DOI: 10.1109/mra.2018.2890460

Datasets

Datasets via OpenAire

sim2real-iCub-iit2

Author(s): Dong Hai Phuong Nguyen

Published in: Zenodo

Imperial-sim2real

Author(s): Dong Hai Phuong Nguyen,Fischer Tobias,Chang Hyung Jin

Published in: Zenodo

sim2real-iCub

Author(s): Dong Hai Phuong Nguyen

Published in: Zenodo

sim2real-iCub-iit

Author(s): Dong Hai Phuong Nguyen

Published in: Zenodo

Project information

SECURE

Grant agreement ID: 642667

Project website

Status

Closed project

Start date

1 September 2015
End date

31 August 2019

Funded under:

H2020-EU.1.3.1.

Overall budget:

€ 3 106 495,20
EU contribution

€ 3 106 495,20

Coordinated by:

UNIVERSITAET HAMBURG

Project information

SECURE

Grant agreement ID: 642667

Project website

Status

Closed project

Start date

1 September 2015
End date

31 August 2019

Funded under:

H2020-EU.1.3.1.

Overall budget:

€ 3 106 495,20
EU contribution

€ 3 106 495,20

Coordinated by:

UNIVERSITAET HAMBURG

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Last update: 4 August 2017

Record number: 197249

CORDIS

Objective

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Participants (6)

Project information

Periodic Reporting for period 1 - SECURE (Safety Enables Cooperation in Uncertain Robotic Environments)

Project information

Deliverables

Publications

Datasets

Project information

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