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Infrastructure Mapping in Well-Structured Environments Using MAV

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Towards Autonomous Robotic Systems (TAROS 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9716))

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Abstract

In this paper, we present a design of a surveying system for warehouse environment using low cost quadcopter. The system focus on mapping the infrastructure of surveyed environment. As a unique and essential parts of the warehouse, pillars from storing shelves are chosen as landmark objects for representing the environment. The map are generated based on fusing the outputs of two different methods, point cloud of corner features from Parallel Tracking and Mapping (PTAM) algorithm with estimated pillar position from a multi-stage image analysis method. Localization of the drone relies on PTAM algorithm. The system is implemented in Robot Operating System(ROS) and MATLAB, and has been successfully tested in real-world experiments. The result map after scaling has a metric error less than 20 cm.

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Authors and Affiliations

  1. School of Information Technology, Halmstad University, Halmsatd, Sweden

    Yuantao Fan, Maytheewat Aramrattana, Saeed Gholami Shahbandi, Hassan Mashad Nemati & Björn Åstrand

Authors
  1. Yuantao Fan
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  2. Maytheewat Aramrattana
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  3. Saeed Gholami Shahbandi
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  4. Hassan Mashad Nemati
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  5. Björn Åstrand
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Corresponding author

Correspondence to Yuantao Fan .

Editor information

Editors and Affiliations

  1. Sheffield Hallam University, Sheffield, United Kingdom

    Lyuba Alboul

  2. University of Sheffield, Sheffield, United Kingdom

    Dana Damian

  3. University of Sheffield, Sheffield, United Kingdom

    Jonathan M. Aitken

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© 2016 Springer International Publishing Switzerland

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Fan, Y., Aramrattana, M., Shahbandi, S.G., Nemati, H.M., Åstrand, B. (2016). Infrastructure Mapping in Well-Structured Environments Using MAV. In: Alboul, L., Damian, D., Aitken, J. (eds) Towards Autonomous Robotic Systems. TAROS 2016. Lecture Notes in Computer Science(), vol 9716. Springer, Cham. https://doi.org/10.1007/978-3-319-40379-3_12

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  • DOI: https://doi.org/10.1007/978-3-319-40379-3_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-40378-6

  • Online ISBN: 978-3-319-40379-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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