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Modeling of a Large Structured Environment

With a Repetitive Canonical Geometric-Semantic Model
  • Saeed Gholami Shahbandi
  • Björn Åstrand
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8717)

Abstract

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.

Keywords

Mobile Robot Extend Kalman Filter Continuous Wavelet Transform Global Constraint Semantic Annotation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Saeed Gholami Shahbandi
    • 1
  • Björn Åstrand
    • 1
  1. 1.Center for Applied Intelligent Systems Research (CAISR), Intelligent Systems LabHalmstad UniversitySweden

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