oru.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Self-sustaining learning for robotic ecologies
Örebro University, School of Science and Technology. (AASS)
Show others and affiliations
2012 (English)Conference paper, Oral presentation only (Refereed)
Abstract [en]

The most common use of wireless sensor networks (WSNs) is to collect environmental data from a specificarea, 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 ofWSN with the concepts and technology of distributed robotics and multi-agent systems can open new waysto design systems able to provide intelligent services in our homes and working places. We also claim thatendowing these systems with learning capabilities can greatly increase their viability and acceptability, bysimplifying design, customization and adaptation to changing user needs. To support these claims, we illus-trate our architecture for an adaptive robotic ecology, named RUBICON, consisting of a network of sensors,effectors and mobile robots.

Place, publisher, year, edition, pages
2012.
Keywords [en]
Robotic Ecology, Wireless Sensor Network, Learning
National Category
Robotics
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-24144OAI: oai:DiVA.org:oru-24144DiVA, id: diva2:541517
Conference
1st International Conference on Sensor Networks (SENSORNETS), 24-26 February, 2012, Rome, Italy
Projects
Rubicon
Funder
EU, FP7, Seventh Framework Programme, 269914Available from: 2012-07-18 Created: 2012-07-18 Last updated: 2017-10-17Bibliographically approved

Open Access in DiVA

No full text in DiVA

Authority records BETA

Broxvall, MathiasSaffiotti, Alessandro

Search in DiVA

By author/editor
Broxvall, MathiasSaffiotti, Alessandro
By organisation
School of Science and Technology
Robotics

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 546 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf