Probabilistic failure isolation for cognitive robots

Dogan Altan, Sanem Sariel-Talay

Araştırma sonucu: ???type-name???Yazıbilirkişi

8 Atıf (Scopus)

Özet

Robots may encounter undesirable outcomes due to failures during the execution of their plans in the physical world. Failures should be detected, and the underlying reasons should be found by the robot in order to handle these failure situations efficiently. Sometimes, there may be more than one cause of a failure, and they are not necessarily related to the action in execution. In this paper, we propose a temporal and Hierarchical Hidden Markov Model (HHMM) based failure isolation method. These HHMMs run in parallel to determine causes of unexpected deviations. Experiments on our Pioneer 3-AT robot show that our method successfully isolates failures suggesting possible causes.

Orijinal dilİngilizce
Sayfalar370-375
Sayfa sayısı6
Yayın durumuYayınlandı - 2014
Etkinlik27th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2014 - Pensacola, United States
Süre: 21 May 201423 May 2014

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???event.eventtypes.event.conference???27th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2014
Ülke/BölgeUnited States
ŞehirPensacola
Periyot21/05/1423/05/14

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Publisher Copyright:
Copyright © 2014, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.

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