| 1. |
- Amato, Giuseppe, et al.
(författare)
-
Robotic UBIquitous COgnitive Network
- 2012
-
Ingår i: Ambient Intelligence. - Berlin, Heidelberg : Springer-Verlag New York. - 9783642287824 - 9783642287831 ; , s. 191-195
-
Konferensbidrag (refereegranskat)abstract
- Robotic ecologies are networks of heterogeneous robotic devices pervasively embedded in everyday environments, where they cooperate to perform complex tasks. While their potential makes them increasingly popular, one fundamental problem is how to make them self-adaptive, so as to reduce the amount of preparation, pre-programming and human supervision that they require in real world applications. The EU FP7 project RUBICON develops self-sustaining learning solutions yielding cheaper, adaptive and efficient coordination of robotic ecologies. The approach we pursue builds upon a unique combination of methods from cognitive robotics, agent control systems, wireless sensor networks and machine learning. This paper briefly illustrates how these techniques are being extended, integrated, and applied to AAL applications.
|
|
| 2. |
- Dragone, Mauro, et al.
(författare)
-
A cognitive robotic ecology approach to self-configuring and evolving AAL systems
- 2015
-
Ingår i: Engineering applications of artificial intelligence. - : Pergamon-Elsevier Science. - 0952-1976 .- 1873-6769. ; 45, s. 269-280
-
Tidskriftsartikel (refereegranskat)abstract
- Robotic ecologies are systems made out of several robotic devices, including mobile robots, wireless sensors and effectors embedded in everyday environments, where they cooperate to achieve complex tasks. This paper demonstrates how endowing robotic ecologies with information processing algorithms such as perception, learning, planning, and novelty detection can make these systems able to deliver modular, flexible, manageable and dependable Ambient Assisted Living (AAL) solutions. Specifically, we show how the integrated and self-organising cognitive solutions implemented within the EU project RUBICON (Robotic UBIquitous Cognitive Network) can reduce the need of costly pre-programming and maintenance of robotic ecologies. We illustrate how these solutions can be harnessed to (i) deliver a range of assistive services by coordinating the sensing & acting capabilities of heterogeneous devices, (ii) adapt and tune the overall behaviour of the ecology to the preferences and behaviour of its inhabitants, and also (iii) deal with novel events, due to the occurrence of new user's activities and changing user's habits.
|
|
