Till Örebro universitet

oru.seÖrebro universitets publikationer
Ändra sökning
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Virtual sensors for human concepts: building detection by an outdoor mobile robot
Örebro universitet, Institutionen för teknik. (Center for Applied Autonomous Sensor Systems)
Department of Computing and Informatics, University of Lincoln, Lincoln, UK.
Örebro universitet, Institutionen för teknik.ORCID-id: 0000-0003-0217-9326
2006 (Engelska)Ingår i: Proceedings of the IROS 2006 workshop: From Sensors toHuman Spatial Concepts, IEEE, 2006, s. 21-26Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

In human–robot communication it is often important to relate robot sensor readings to concepts used by humans. We suggest the use of a virtual sensor (one or several physical sensors with a dedicated signal processing unit for the recognition of real world concepts) and a method with which the virtual sensor can learn from a set of generic features. The virtual sensor robustly establishes the link between sensor data and a particular human concept. In this work, we present a virtual sensor for building detection that uses vision and machine learning to classify the image content in a particular direction as representing buildings or non-buildings. The virtual sensor is trained on a diverse set of image data, using features extracted from grey level images. The features are based on edge orientation, the configurations of these edges, and on grey level clustering. To combine these features, the AdaBoost algorithm is applied. Our experiments with an outdoor mobile robot show that the method is able to separate buildings from nature with a high classification rate, and to extrapolate well to images collected under different conditions. Finally, the virtual sensor is applied on the mobile robot, combining its classifications of sub-images from a panoramic view with spatial information (in the form of location and orientation of the robot) in order to communicate the likely locations of buildings to a remote human operator.

Ort, förlag, år, upplaga, sidor
IEEE, 2006. s. 21-26
Nyckelord [en]
Human–robot communication, Human concepts, Virtual sensor, Automatic building detection, AdaBoost
Nationell ämneskategori
Teknik och teknologier Data- och informationsvetenskap
Forskningsämne
Datalogi
Identifikatorer
URN: urn:nbn:se:oru:diva-3958OAI: oai:DiVA.org:oru-3958DiVA, id: diva2:138257
Konferens
IROS Workshop: From Sensors to Human Spatial Concepts, Beijing, China, October 10, 2006
Tillgänglig från: 2007-08-27 Skapad: 2007-08-27 Senast uppdaterad: 2018-06-11Bibliografiskt granskad

Open Access i DiVA

Virtual Sensors for Human Concepts: Building Detection by an Outdoor Mobile Robot(429 kB)492 nedladdningar
Filinformation
Filnamn FULLTEXT01.pdfFilstorlek 429 kBChecksumma SHA-512
da0c63449b5e93bcfc42adb8d783bb512d77a173ca9f5f866a69852f1bb73405f271e80bd9bd698bf38e2a83e07db11956049ed0b0f1d636a014f4cb37eaa78f
Typ fulltextMimetyp application/pdf

Person

Persson, MartinLilienthal, Achim J.

Sök vidare i DiVA

Av författaren/redaktören
Persson, MartinLilienthal, Achim J.
Av organisationen
Institutionen för teknik
Teknik och teknologierData- och informationsvetenskap

Sök vidare utanför DiVA

GoogleGoogle Scholar
Totalt: 492 nedladdningar
Antalet nedladdningar är summan av nedladdningar för alla fulltexter. Det kan inkludera t.ex tidigare versioner som nu inte längre är tillgängliga.

urn-nbn

Altmetricpoäng

urn-nbn
Totalt: 672 träffar
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf