Automated Bayesian network integration based on ontology for reasoning object existence of service R

Youn Suk Song, Sung Bae Cho

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Object detection of service robots is very important for their service. Most of services such as delivery, errand of users are related to objects. Conventional methods are based on the geometric models in static industrial environments, but they have limitations in uncertain and dynamic indoor environments, because interest object can be occluded or small in the image according to the robot's location or angle. For solving these uncertain situations, it is helpful to predict the probability of target object, because it can give important information for their next action. Our idea is to use observed objects as context information for predicting target one. For this, we adopt Bayesian networks and ontology together for modeling domain knowledge and reasoning objects in probabilistic frame. We verified the performance and process of our method through the experiments.

Original languageEnglish
Title of host publicationProceedings of the 17th World Congress, International Federation of Automatic Control, IFAC
Edition1 PART 1
DOIs
Publication statusPublished - 2008 Dec 1
Event17th World Congress, International Federation of Automatic Control, IFAC - Seoul, Korea, Republic of
Duration: 2008 Jul 62008 Jul 11

Publication series

NameIFAC Proceedings Volumes (IFAC-PapersOnline)
Number1 PART 1
Volume17
ISSN (Print)1474-6670

Other

Other17th World Congress, International Federation of Automatic Control, IFAC
CountryKorea, Republic of
CitySeoul
Period08/7/608/7/11

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering

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    Song, Y. S., & Cho, S. B. (2008). Automated Bayesian network integration based on ontology for reasoning object existence of service R. In Proceedings of the 17th World Congress, International Federation of Automatic Control, IFAC (1 PART 1 ed.). (IFAC Proceedings Volumes (IFAC-PapersOnline); Vol. 17, No. 1 PART 1). https://doi.org/10.3182/20080706-5-KR-1001.2476