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Modeling of a Large Structured Environment

With a Repetitive Canonical Geometric-Semantic Model

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNAI,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.

This work as a part of AIMS project, is supported by the Swedish Knowledge Foundation and industry partners Kollmorgen, Optronic, and Toyota Material Handling Europe.

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© 2014 Springer International Publishing Switzerland

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Shahbandi, S.G., Åstrand, B. (2014). Modeling of a Large Structured Environment. In: Mistry, M., Leonardis, A., Witkowski, M., Melhuish, C. (eds) Advances in Autonomous Robotics Systems. TAROS 2014. Lecture Notes in Computer Science(), vol 8717. Springer, Cham. https://doi.org/10.1007/978-3-319-10401-0_1

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  • DOI: https://doi.org/10.1007/978-3-319-10401-0_1

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10400-3

  • Online ISBN: 978-3-319-10401-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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