Europe 2014-2020: robotique
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Commission Européenne, présentations de la Délégation générale Société de l’Information à la délégation d’Aquitains conduite par AEC, 30 janvier 2012: robotique
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Europe 2014-2020: robotique
- 1. Soutien européen à la robotique Olivier DA COSTA Project Officer Commission Européenne Direction générale Société de l‘Information et Médias Unité E5 – Systèmes Cognitifs Systems, Interaction, Robotiques Olivier.da-costa@ec.europa.eu ••• 1
- 2. La robotique : Technologie essentielle pour l’Europe Marché en forte croissance, porteur d’emploi: – robots industriels, de service, ménager: croissance attendue de 60% jusqu’à 2015 – tiré par une demande croissante • Productivité, qualité, qualité de travail, … • Besoins sociétaux: santé, démographie, sécurité, .. – alimenté par le développement technologique • plus “intelligents”, adaptifs, robustes, intuitifs, moins chers… Pas d’acteurs industriels dominant (jusqu’à présent) Technologie déterminante pour l’avenir du secteur ICT – Espaces intelligents, interfaces intuitives, apprenant par apprentissage… Technologie essentielle pour le maintien de la production en Europe ••• 2
- 3. Participation en Robotique et Systèmes cognitifs ETATS-MEMBRES Participation dans les projets européens 1 GERMANY 27,4% 2 UNITED KINGDOM 17,3% 3 ITALY 12,4% 4 SWITZERLAND 6,2% 5 FRANCE 5,6% 6 SWEDEN 4,9% 7 SPAIN 3,7% 8 BELGIUM 3,2% 9 NETHERLANDS 3,2% 10 AUSTRIA 3,1% 3 •••
- 4. Objectif “Cognitive Systems & Robotics” Trois types de soutien Recherche: Fondamentale RDI industrielle Réseautage & renforcement de la communauté Collaboration plus efficace entre recherches académique et industrielle ••• 4
- 5. Objectif “Cognitive Systems & Robotics” ► About 150 funded projects Portefeuille de projets UNDERSTANDING ► About 100 ongoing projects • Recognising ► With about 1000 • Interpreting participants UNDERSTANDING • Adapting • Planning ► Total EU funding over 500 • Modelling M€ • Cognitive architectures COGNITIVE PERCEIVING SYSTEMS PERCEIVING ACTING • Touching & • Seeing ROBOTICS • Hearing • Distributed sensing • Advanced sensing ACTING LEARNING • Manipulating APPLICATION AREAS • Navigating •Aerial • Interacting •Underwater • Collaborating •Industry and manufacturing • Monitoring •Professional and domestic services •Medical and rehabilitation •Monitoring and surveillance ••• 5 http://cordis.europa.eu/fp7/ict/cognition/projects/areas-projects_en.html
- 6. Objectif “Cognitive Systems & Robotics” Réseautage & renforcement de la communauté EUROP - European Robotics Technology Platform EURON - EUropean RObotics research Network euRobotics - European Robotics Coordination Action EUCogIII - European Network for the Advancement of Artificial Cognitive Systems, Interaction and Robotics + Echord - European Clearing House for Open Robotics Development ••• 6
- 7. Objectif “Cognitive Systems & Robotics” - Call 9 OBJECTIVE: 2.1 Cognitive Systems and Robotics PUBLICATION: 18/01/2012 DEADLINE: 17/04/2012 INDICATIVE BUDGET: 82 M€ (80M€ (STREPS + IPs) – 2M€CAs) • Target (b) Cognition and control in complex systems - STREPs + IPs • Target (c) Gearing up and accelerating cross- fertilisation between academic and industrial robotics research - IPs • Target (e) Speeding up progress towards smarter robots through targeted competitions - CAs ••• 7
- 8. Merci! ••• 8
- 9. Les chiffres Les robots industriels – 2010: ± 118,000 nouvelles unités vendues, • ~ $5.7 milliards, +97% comparé à 2009 – Marché mondial estimé à $17.5 milliards (2011) • Croissance de 40% d’ici 2014 Les robots de service professionnel – Croissance de 7% en 2010 et de 60% d’ici 2014 – Marché mondial estimé à $16 milliards • (± 90,000 unités sans les robots ménagers et de loisir) Les robots ménagers – Croissance de 26% en 2010 – > 60% entre 2011et 2015 ••• 9
- 10. Call 9 - Target (b): Cognition and control in complex systems (STREPs + IPs) • Acquisition and application of cognitive capabilities (e.g., perception, conceptualisation, reasoning, planning) • Enhance performance and manageability of complex multi-component and multi- degree-of freedom artificial systems • Synergies: cognitive systems - systems control engineering ••• 10
- 11. Call 9 - Target (c): Gearing up and accelerating cross-fertilisation between academic and industrial robotics research (IPs) • Joint industrially-relevant scenarios • Shared research infrastructure • Experimentation with industrial platforms • Benchmarking ••• 11
- 12. Call 9 - Target (e): Speeding up progress towards smarter robots through targeted competitions (CAs) GOAL –> tool to support science • Not just ‘nuts-and-bolts’ engineering Objective Comparison of results Measure & Ensure progress Share results VISIBILITY ••• 12
Notes de l'éditeur
- Industrial robotics companies today derive much of their revenues from the automotive manufacturing sector, where robots perform tasks such as material handling, spot-welding, assembly and painting. Overall, there are 1 million industrial robots installed worldwide, valued at about $30 billion. In 2010, 118,000 new units were sold worth $5.7 billion, an increase of 97% compared to 2009. The world market for robotic systems is estimated to be about $17.5 billion in 2011. The sales of industrial robots are expected to increase by 17% this year and by a further 40% until 2014 and are expected to expand further to other manufacturing sectors. European robot manufacturers are strong in industrial robotics with a market share of about 25% in newly sold systems
- Research Rationale By promoting research into systems that have cognitive functions normally associated with people or animals and which exhibit a high degree of robustness in coping with unpredictable situations, we seek to overcome limitations of today's computers, robots, and other man-made creations to handle simple everyday situations with common sense and to work without pre-programming in natural surroundings, while maintaining and possibly improving the quality of their services. Unit Mission We support research on the development and construction of robotic systems and other artificial cognitive systems than can process and interpret various kinds of sensor data (images, speech and other forms of sensor data), and act purposefully and autonomously towards achieving goals. Such systems are to operate in dynamic real-life environments and are to be capable of responding timely and sensibly to gaps in their knowledge and to situations that have not been anticipated at design time. These systems should learn and develop through individual or social interaction with their environment. The work provides an enabling technology that applies across domains such as industrial and service robotics, automation, image recognition, systems monitoring and control, automated reasoning and decision support, and natural language understanding. The work could furthermore borrow insights from the bio-sciences, and yield innovative insights about perception, understanding, interaction, learning and knowledge representation to further underpin progress towards engineering systems with the desired capabilities.
- Industrial robotics companies today derive much of their revenues from the automotive manufacturing sector, where robots perform tasks such as material handling, spot-welding, assembly and painting. Overall, there are 1 million industrial robots installed worldwide, valued at about $30 billion. In 2010, 118,000 new units were sold worth $5.7 billion, an increase of 97% compared to 2009. The world market for robotic systems is estimated to be about $17.5 billion in 2011. The sales of industrial robots are expected to increase by 17% this year and by a further 40% until 2014 and are expected to expand further to other manufacturing sectors. European robot manufacturers are strong in industrial robotics with a market share of about 25% in newly sold systems
- Overhead by infrastructure that had to be built? cooperation with SMEs tend to be more successful academia-driven cooperation tend to be more successful (see US experience)
- CHALLENGES better than COMPETITIONS Important to run the competition several times. This should be a firm requirement. Careful about over-fitting on data-sets What are the measures? Tuning of the level of difficulty is critical: it needs to be hard to connect to deep issues, but not too hard to be relevant to current methodologies. - Pascal was a breakthrough and changed the field when introduced. Now it is deteriorated to a stage of adding of a feature to increase performance by Epsylon Challenges increase visibility of the field and give the opportunity to small players to be highlighted Regardless of the difficulty, you should take a risk. You can never predict the outcome.