Multi-Sensor Surveillance of Indoor Environments by an Autonomous Mobile Robot (Articolo in rivista)

Type
Label
  • Multi-Sensor Surveillance of Indoor Environments by an Autonomous Mobile Robot (Articolo in rivista) (literal)
Anno
  • 2010-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1504/IJISTA.2010.030187 (literal)
Alternative label
  • Donato Di Paola; David Naso; Annalisa Milella; Grazia Cicirelli; Arcangelo Distante (2010)
    Multi-Sensor Surveillance of Indoor Environments by an Autonomous Mobile Robot
    in International journal of intelligent systems technologies and applications (Print)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Donato Di Paola; David Naso; Annalisa Milella; Grazia Cicirelli; Arcangelo Distante (literal)
Pagina inizio
  • 18 (literal)
Pagina fine
  • 35 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://inderscience.metapress.com/content/2j331404v5p23808/?p=f3ab300b9956440a8d948fa870973fbc&pi=0 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 8 (literal)
Rivista
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo
  • 1-4 (literal)
Note
  • Google Scholar (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • ISSIA - CNR; POLITECNICO DI BARI; ISSIA - CNR; ISSIA - CNR (literal)
Titolo
  • Multi-Sensor Surveillance of Indoor Environments by an Autonomous Mobile Robot (literal)
Abstract
  • An autonomous mobile robotic system for surveillance of indoor environments is presented. Applications of the proposed system include surveillance of large environments such as airports, museums and warehouses. A multi-layer decision scheme controls different surveillance tasks. In particular, this paper focuses on two main functions: building an augmented map of the environment and monitoring specific areas of interest to detect unexpected changes based on visual and laser data. The effectiveness of the system is demonstrated through experimental tests. The results are promising, proving the proposed methods to be successful in detecting either new or removed objects in the surveyed scene. It is also shown that the robotic surveillance system is able to address a number of specific problems related to environment mapping, autonomous navigation and scene processing, and could be effectively employed for real-world surveillance applications. (literal)
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