RT Conference Proceedings
T1 Self-sustaining learning for robotic ecologies
A1 Bacciu, D.
A1 Broxvall, M.
A1 Coleman, S.
A1 Dragone, M.
A1 Gallicchio, C.
A1 Gennán, R.
A1 Loparo, C.
A1 Guzmez, R.
A1 Lozano-Peiteado, H.
A1 Ray, A.
A1 Renteria, A.
A1 Saffiotti, A.
A1 Vairo, C.
AB The most common use of wireless sensor networks (WSNs) is to collect environmental data from a specific area, and to channel it to a central processing node for on-line or off-line analysis. The WSN technology, however, can be used for much more ambitious goals. We claim that merging the concepts and technology of WSN with the concepts and technology of distributed robotics and multi-agent systems can open new ways to design systems able to provide intelligent services in our homes and working places. We also claim that endowing these systems with learning capabilities can greatly increase their viability and acceptability, by simplifying design, customization and adaptation to changing user needs. To support these claims, we illustrate our architecture for an adaptive robotic ecology, named RUBICON, consisting of a network of sensors, effectors and mobile robots.
SN 9789898565013
YR 2012
FD 2012
LK https://hdl.handle.net/11556/2087
UL https://hdl.handle.net/11556/2087
LA eng
NO Bacciu , D , Broxvall , M , Coleman , S , Dragone , M , Gallicchio , C , Gennán , R , Loparo , C , Guzmez , R , Lozano-Peiteado , H , Ray , A , Renteria , A , Saffiotti , A & Vairo , C 2012 , Self-sustaining learning for robotic ecologies . in SENSORNETS 2012 - Proceedings of the 1st International Conference on Sensor Networks . SENSORNETS 2012 - Proceedings of the 1st International Conference on Sensor Networks , pp. 99-103 , 1st International Conference on Sensor Networks, SENSORNETS 2012 , Rome , Italy , 24/02/12 .
NO conference
DS TECNALIA Publications
RD 28 jul 2024