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Volume 7 Issue 4
Jun.  2020

IEEE/CAA Journal of Automatica Sinica

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Chinthaka Premachandra, Dang Ngoc Hoang Thanh, Tomotaka Kimura and Hiroharu Kawanaka, "A Study on Hovering Control of Small Aerial Robot by Sensing Existing Floor Features," IEEE/CAA J. Autom. Sinica, vol. 7, no. 4, pp. 1016-1025, July 2020. doi: 10.1109/JAS.2020.1003240
Citation: Chinthaka Premachandra, Dang Ngoc Hoang Thanh, Tomotaka Kimura and Hiroharu Kawanaka, "A Study on Hovering Control of Small Aerial Robot by Sensing Existing Floor Features," IEEE/CAA J. Autom. Sinica, vol. 7, no. 4, pp. 1016-1025, July 2020. doi: 10.1109/JAS.2020.1003240

A Study on Hovering Control of Small Aerial Robot by Sensing Existing Floor Features

doi: 10.1109/JAS.2020.1003240
Funds:  This work was partially supported by Branding Research Fund by Shibaura Institute of Technology (SIT)
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  • Since precise self-position estimation is required for autonomous flight of aerial robots, there has been some studies on self-position estimation of indoor aerial robots. In this study, we tackle the self-position estimation problem by mounting a small downward-facing camera on the chassis of an aerial robot. We obtain robot position by sensing the features on the indoor floor. In this work, we used the vertex points (tile corners) where four tiles on a typical tiled floor connected, as an existing feature of the floor. Furthermore, a small lightweight microcontroller is mounted on the robot to perform image processing for the on-board camera. A lightweight image processing algorithm is developed. So, the real-time image processing could be performed by the microcontroller alone which leads to conduct on-board real time tile corner detection. Furthermore, same microcontroller performs control value calculation for flight commanding. The flight commands are implemented based on the detected tile corner information. The above mentioned all devices are mounted on an actual machine, and the effectiveness of the system was investigated.

     

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    Highlights

    • Hovering Control of Small Aerial Robot.
    • Image Processing Using Small-type and Low-weight Microcontrollers.
    • Specific Image Feature Point Detection by Weak Directional Pattern Analysis.
    • On-board Camera Image Processing Based Autonomous Flight Control of UAV.
    • Simple and Low-cost Image Noise Removal Process.

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