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Trends & Issues in the integration between
Service Robots
and
Smart Environments
Track 3 – 13 March 8:30-10:30
Mauro
Drago...
MOBISERV
Motivations
Different viewpoints:
● People-centered initiatives, HRI
● Development of specific services
● Service-agnostic efforts
● …...
Identify common R&D agenda
●State of the art: Lessons learned, mature
knowledge, tools, shareable results...
●Issues preve...
●8.30-8:40 Welcome and introduction
●8.40-9.45 Talks by invited speakers
9 speakers, 5 minutes each !!!!
1) Your project: ...
Contribute to MAR & Related Topic Groups
●Memo for Wiki, from minutes of this workshop,
in terms of:
1) State of the art: ...
Speakers
● Arantxa Renteria & Mauro Dragone, RUBICON
● Markus Vincze, HOBBIT
● Atta Badi, CompanionAble
● Sanja Dogramadzi...
RUBICON ICT-2009.2.1 (269914)
Robotic UBIquitous Cognitive Network
School of Computer Science and Informatics.
University ...
Reduce need for

Reprogramming

Configuration

Maintenance

Supervision
Over time, the ecology adapts to
changes in it...
Test-Beds
RUBICON is validated in in two real-world test-beds
• Ambient Assisted Living
in sensorised apartments
• In-Hosp...
Approach: Requirements & Architecture
for an Autonomous, Self-Adaptive Smart
Environment
Approach: Requirements & Architecture
for an Autonomous, Self-Adaptive Smart
Environment
Bind components and enable
commun...
Approach: Requirements & Architecture
for an Autonomous, Self-Adaptive Smart
Environment
Find and monitor plans
to carry o...
Approach: Requirements & Architecture
for an Autonomous, Self-Adaptive Smart
Environment
Learn to
recognize
the situation ...
Approach: Requirements & Architecture
for an Autonomous, Self-Adaptive Smart
Environment
Learn to
recognize
what service
t...
Components
Communication Layer:
Peer-to-peer tuplespace (PEIS)
+ WSN middleware
(IEEE 802.15.4 compliant)
+ Proxy for domo...
Open Questions & Opportunities
1) The system is evaluated in realistic environments but
not yet used in real applications
...
Trends & Issues in the integration between Service Robots and Smart Environments
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Trends & Issues in the integration between Service Robots and Smart Environments

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Trends & Issues in the integration between Service Robots and Smart Environments

  1. 1. Trends & Issues in the integration between Service Robots and Smart Environments Track 3 – 13 March 8:30-10:30 Mauro Dragone Arantxa Renteria http://fp7rubicon.eu
  2. 2. MOBISERV Motivations
  3. 3. Different viewpoints: ● People-centered initiatives, HRI ● Development of specific services ● Service-agnostic efforts ● … Motivations
  4. 4. Identify common R&D agenda ●State of the art: Lessons learned, mature knowledge, tools, shareable results... ●Issues preventing further progress, e.g. concerning interoperability, personalization, adaptation ... ●Opportunities, to take advantage and combine past advancements in the area, open new applications... Goals
  5. 5. ●8.30-8:40 Welcome and introduction ●8.40-9.45 Talks by invited speakers 9 speakers, 5 minutes each !!!! 1) Your project: goals and approach 2) Lessons learned, (shareable) results/tools 3) Open questions & Opportunities ●9.45-10.20 Discussion ●10:20-10.30 Conclusion Agenda
  6. 6. Contribute to MAR & Related Topic Groups ●Memo for Wiki, from minutes of this workshop, in terms of: 1) State of the art: technologies and abilities particular to this type of project 2) Issues / step changes 3) Opportunities / Possible impact of integrated approaches Proposed Outcome
  7. 7. Speakers ● Arantxa Renteria & Mauro Dragone, RUBICON ● Markus Vincze, HOBBIT ● Atta Badi, CompanionAble ● Sanja Dogramadzi, MOBISERV ● Melvin Isken, FLORENCE ● Kerstin Dautenhahn, ACCOMPANY ● Andrea Orlandini, Giraffe+ ● Paulo Alvito, MOnarCH ● Filippo Cavallo, Robot-ERA
  8. 8. RUBICON ICT-2009.2.1 (269914) Robotic UBIquitous Cognitive Network School of Computer Science and Informatics. University College Dublin (UCD) 13 March 2014, Rovereto, ERF-13 Dr. Mauro Dragone RUBICON Scientific Leader
  9. 9. Reduce need for  Reprogramming  Configuration  Maintenance  Supervision Over time, the ecology adapts to changes in its environment, to the user's needs, and improves the way It carries out its services RUBICON GOAL: Self-Adaptive Robotic Ecologies Increase  Adaptability  Flexibility  Robustness  Open new application areas
  10. 10. Test-Beds RUBICON is validated in in two real-world test-beds • Ambient Assisted Living in sensorised apartments • In-Hospital Transport System (ROBOTNIK)
  11. 11. Approach: Requirements & Architecture for an Autonomous, Self-Adaptive Smart Environment
  12. 12. Approach: Requirements & Architecture for an Autonomous, Self-Adaptive Smart Environment Bind components and enable communications with sensors, actuators and robots
  13. 13. Approach: Requirements & Architecture for an Autonomous, Self-Adaptive Smart Environment Find and monitor plans to carry out useful services
  14. 14. Approach: Requirements & Architecture for an Autonomous, Self-Adaptive Smart Environment Learn to recognize the situation of the environment and of the user, from experience
  15. 15. Approach: Requirements & Architecture for an Autonomous, Self-Adaptive Smart Environment Learn to recognize what service to achieve in each situation (e.g. to assist the user)
  16. 16. Components Communication Layer: Peer-to-peer tuplespace (PEIS) + WSN middleware (IEEE 802.15.4 compliant) + Proxy for domotic KNX Learning Layer: A distributed, adaptive sensor fusion and learning infrastructure used for event prediction, localization, and activity recogniton Control Layer: Central configuration planner with multiple solvers + multi-agent system Cognitive Layer: Based on Self-Organized Fuzzy Neural Networks (SOFNN)
  17. 17. Open Questions & Opportunities 1) The system is evaluated in realistic environments but not yet used in real applications 2) Not yet integrated with AAL infrastructures, e.g. UniversAAL 3) Learning takes time ... 4) HRI is not a focus - it may help to accelerate learning - from technological-driven to people-centric 5) Rubicon could support online personalization / adaptation of existing solutions.

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