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ROS-Gazebo Supported Platform for Tag-in-Loop Indoor Localization of Quadrocopter

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Book cover Intelligent Autonomous Systems 14 (IAS 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 531))

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Abstract

Localization and navigation inside GPS-denied buildings has been one of the main technological challenges of quadrocopter researches. Hereafter, this paper proposes and develops a supporting research platform integrated with 2D tag visual fiducials for quadrocopter indoor autonomous localization. Robot operating system (ROS) and Gazebo are simultaneously fused into the integrated platform. Under such circumstances, tag-involved images are sequentially captured via on-board cameras, while vehicle position/posture is achieved via off-board processing based on the open-source AprilTag algorithm. Simulation and experiments of the AR.Drone 2.0 are conducted to demonstrate the system architecture and workflow of the developed tag-in-loop indoor localization research platform. The results validate the effectiveness and application potentials of the ROS-Gazebo platform to support quadrocopters’ autonomous indoor localization, flight autopilot, and cooperative control, etc.

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Authors and Affiliations

  1. College of Mechatronics and Automation, National University of Defense Technology, 410073, Changsha, China

    Shuyuan Wang & Tianjiang Hu

Authors
  1. Shuyuan Wang
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  2. Tianjiang Hu
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Corresponding author

Correspondence to Tianjiang Hu .

Editor information

Editors and Affiliations

  1. Shanghai Jiao Tong University , Shanghai, China

    Weidong Chen

  2. Osaka University , Osaka, Japan

    Koh Hosoda

  3. University of Padua , Padua, Italy

    Emanuele Menegatti

  4. Osaka University , Osaka, Japan

    Masahiro Shimizu

  5. Shanghai Jiao Tong University , Shanghai, China

    Hesheng Wang

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Wang, S., Hu, T. (2017). ROS-Gazebo Supported Platform for Tag-in-Loop Indoor Localization of Quadrocopter. In: Chen, W., Hosoda, K., Menegatti, E., Shimizu, M., Wang, H. (eds) Intelligent Autonomous Systems 14. IAS 2016. Advances in Intelligent Systems and Computing, vol 531. Springer, Cham. https://doi.org/10.1007/978-3-319-48036-7_14

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  • DOI: https://doi.org/10.1007/978-3-319-48036-7_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-48035-0

  • Online ISBN: 978-3-319-48036-7

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