View source for Publications:Modeling of a Large Structured Environment : With a Repetitive Canonical Geometric-Semantic Model

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{{PublicationSetupTemplate|Author=Björn Åstrand, Saeed Gholami Shahbandi
|PID=741871
|Name=Åstrand, Björn [bjorn] (Högskolan i Halmstad [2804], Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE) [3905], Halmstad Embedded and Intelligent Systems Research (EIS) [3938], CAISR Centrum för tillämpade intelligenta system (IS-lab) [13650]);Gholami Shahbandi, Saeed [saesha] (Högskolan i Halmstad [2804], Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE) [3905], Halmstad Embedded and Intelligent Systems Research (EIS) [3938], CAISR Centrum för tillämpade intelligenta system (IS-lab) [13650])
|Title=Modeling of a Large Structured Environment : With a Repetitive Canonical Geometric-Semantic Model
|PublicationType=Conference Paper
|ContentType=Refereegranskat
|Language=eng
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|Conference=TAROS 2014 Towards Autonomous Robotic Systems
|StartPage=1
|EndPage=12
|Year=2014
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|Publisher=Springer
|Series=LNAI ; 8717
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|NBN=urn:nbn:se:hh:diva-26321
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|Categories=Signalbehandling (20205)
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|Projects=AIMS
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|Abstract=<p>AIMS project attempts to link the logistic requirements of an intelligent warehouse and state of the art core technologies of automation, by providing an awareness of the environment to the autonomous systems and vice versa. In this work we investigate a solution for modeling the infrastructure of a structured environment such as warehouses, by the means of a vision sensor. The model is based on the expected pattern of the infrastructure, generated from and matched to the map. Generation of the model is based on a set of tools such as closed-form Hough transform, DBSCAN clustering algorithm, Fourier transform and optimization techniques. The performance evaluation of the proposed method is accompanied with a real world experiment.</p>
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|CreatedDate=2014-08-29
|PublicationDate=2014-08-29
|LastUpdated=2014-08-29
|diva=http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:741871}}
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