Consiglio Nazionale delle Ricerche

Tipo di prodottoArticolo in rivista
TitoloDifferent learning methodologies for vision-based navigation behaviors
Anno di pubblicazione2005
FormatoCartaceo
Autore/iG. Cicirelli, T. D’Orazio, A. Distante
Affiliazioni autoriISSIA CNR
Autori CNR e affiliazioni
  • ARCANGELO DISTANTE
  • TIZIANA RITA D'ORAZIO
  • GRAZIA CICIRELLI
Lingua/e
  • inglese
AbstractIn this work the complex behavior of localizing a mobile vehicle with respect to the door of the environment and then reaching the door has been developed. The robot uses visual information to detect and recognize the door and to determine its state with respect to it. This complex task has been divided into two separate behaviors: door-recognition and door-reaching. A supervised methodology based on learning by components has been applied for recognizing the door. Learning by components allows to recognize the door also in difficult situations such as partial occlusions and besides, it makes recognition independent of viewpoint variations and scale changes. An unsupervised methodology based on reinforcement learning has been used for the door-reaching behavior, instead. The image of the door gives information about the relative position of the vehicle with respect to the door. Then the Q-learning algorithm is used to generate the optimal state-action associations. The problem of defining the state and the action sets has been addressed with the aim of producing smooth paths, of reducing the effects of visual errors during real navigation, and of keeping low the computational cost during the learning phase. A novel way to obtain a continuous action set has been introduced: it uses a fuzzy model to evaluate the system state. Experimental results in real environment show both the robustness of the door-recognition behavior and the generality of the door-reaching behavior.
Lingua abstractinglese
Altro abstract-
Lingua altro abstract-
Pagine da1
Pagine a26
Pagine totali-
RivistaInternational journal of pattern recognition and artificial intelligence
Attiva dal 1987
Editore: World Scientific. - Singapore
Paese di pubblicazione: Singapore
Lingua: inglese
ISSN: 0218-0014
Titolo chiave: International journal of pattern recognition and artificial intelligence
Titolo abbreviato: Int. j. pattern recogn. artif. intell.
Numero volume della rivista19
Fascicolo della rivista8
DOI10.1142/S021800140500440X
Verificato da referee-
Stato della pubblicazione-
Indicizzazione (in banche dati controllate)
  • ISI Web of Science (WOS) (Codice:000234753600001)
  • Scopus (Codice:2-s2.0-29344445215)
Parole chiaveNeural networks, learning by components, reinforcement learning, behavior-based navigation
Link (URL, URI)-
Titolo parallelo-
Licenza-
Scadenza embargo-
Data di accettazione-
Note/Altre informazioni-
Strutture CNR
  • ISSIA — Istituto di studi sui sistemi intelligenti per l'automazione
Moduli/Attività/Sottoprogetti CNR
  • SP.P06.004.001 : Sistemi Intelligenti per la sicurezza
Progetti Europei-
Allegati
Articolo pubblicato (documento privato )
Descrizione: Articolo su Rivista
Tipo documento: application/octetstream

Dati storici
I dati storici non sono modificabili, sono stati ereditati da altri sistemi (es. Gestione Istituti, PUMA, ...) e hanno solo valore storico.
Rivista ISIINTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE [11472J0]