NDLI: Bayesian-Based Decision-Making for Object Search and Classification

Content Provider	IEEE Xplore Digital Library
Author	Yue Wang Hussein, I.I.
Copyright Year	1993
Abstract	This paper focuses on the development of real-time decision-making criteria for an autonomous vehicle whose tasks to be performed are competing under limited sensory resources. More specifically, we are interested in the search and classification of multiple static objects of unknown number and positions given a single autonomous sensor vehicle. In this case, search and classification are two competing demands since an autonomous vehicle can perform either task but not both at the same time. During a search task, once the vehicle finds an object of interest, it has to decide on whether to neglect the found object and continue searching, or stop and observe that object. If the vehicle decides to stop and classify the object, it has to decide on how much time it can afford to do so. This is a very critical decision as choosing one option over the other may mean missing other, more important objects not yet found, or missing the opportunity to satisfactorily classify a found critical object. Building on previous deterministic work by the authors, in this paper we develop Bayesian-based probabilistic and information-theoretic search versus classification decision-making criteria that result in guaranteed detection and classification of all the unknown objects in the domain. Simulation-based results are provided to study the performance of the proposed decision-making strategy.
Sponsorship	IEEE Control Systems Society
Starting Page	1639
Ending Page	1647
Page Count	9
File Size	1538197
File Format	PDF
ISSN	10636536
Volume Number	19
Issue Number	6
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-11-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Mobile robots Search problems Uncertainty Decision making Bayesian methods Surveillance Real time systems surveillance Autonomous vehicles Bayes procedures decision-making information theory and control
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Electrical and Electronic Engineering

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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