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Mono Camera Based Pallet Detection and Pose Estimation for Automated Guided Vehicles

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LISS 2020

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Abstract

Detection and pose estimation of pallets are critical phases in the operation of automated guided vehicles. In this paper, we introduce a novel pipeline for accurate localization based on only a single camera. We utilize the popular YOLO detector, object, and camera models to achieve better performance than the state of the art techniques.

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Acknowledgements

Project no. 2017-1.3.1-VKE-2017-00036 has been implemented with the support provided from the National Research, Development and Innovation Fund of Hungary, financed under the VKE_17 funding scheme.

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Authors and Affiliations

  1. Faculty of Transportation Engineering and Vehicle Engineering, Budapest University of Technology and Economics Budapest, Budapest, Hungary

    Gabor Bohacs, Zoltan Rozsa & Balint Bertalan

Authors
  1. Gabor Bohacs
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  2. Zoltan Rozsa
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  3. Balint Bertalan
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Corresponding author

Correspondence to Gabor Bohacs .

Editor information

Editors and Affiliations

  1. Beijing Jiaotong University, Beijing, China

    Shifeng Liu

  2. Budapest University of Technology and Economics, Budapest, Hungary

    Gábor Bohács

  3. Beijing Jiaotong University, Beijing, China

    Xianliang Shi

  4. International Center for Informatics Research, Beijing Jiaotong University, Beijing, China

    Xiaopu Shang

  5. Beijing Logistics Informatics Research Base, Beijing Jiaotong University, Beijing, China

    Anqiang Huang

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Bohacs, G., Rozsa, Z., Bertalan, B. (2021). Mono Camera Based Pallet Detection and Pose Estimation for Automated Guided Vehicles. In: Liu, S., Bohács, G., Shi, X., Shang, X., Huang, A. (eds) LISS 2020. Springer, Singapore. https://doi.org/10.1007/978-981-33-4359-7_1

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