A journal of IEEE and CAA , publishes high-quality papers in English on original theoretical/experimental research and development in all areas of automation
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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  • [1]
    Z. F. He, L. Zhao, and L. Zhao, “Robust chattering free backstepping/backstepping sliding mode control for quadrotor hovering, ” in Proc. IEEE Information Technology, Networking, Electronic and Automation Control Conf., pp. 616–620, May. 2016.
    D. Iosifidis, N. Alvanos, C. Yfoulis, S. Papadopoulou, and C. Galatsopoulos, “Practical PID hovering control of a laboratory quadcopter using low-cost embedded control hardware and software, ” in Proc. UKACC 12th Int. Conf. Control (CONTROL), pp. 428–433, Sept. 2018.
    S. A. Hadiwardoyo, C. T. Calafate, J. C. Cano, K. Krinkin, D. Klionskiy, E. H. Orallo, and P. Manzoni, “Optimizing UAV-to-car communications in 3D environments through dynamic UAV positioning, ” in Proc. IEEE/ACM 23rd Int. Symp. Distributed Simulation and Real Time Applications, Oct. 2019.
    N. Gageik, P. Benz, and S. Montenegro, “Obstacle detection and collision avoidance for a UAV with complementary low-cost sensors,” IEEE Access, vol. 3, pp. 599–609, 2015. doi: 10.1109/ACCESS.2015.2432455
    A. Devos, E. Ebeid, and P. Manoonpong, “Development of autonomous drones for adaptive obstacle avoidance in real world environments, ” in Proc. 21st Euromicro Conf. Digital System Design, pp. 707–710, Aug. 2018.
    E. pall, K. mathe, L. tamas, and L. busoniu, “Railway track following with the AR.Drone using vanishing point detection, ” in Proc. IEEE Int. Conf. Automation, Quality and Testing, Robotics, pp. 1–6, May 2014.
    T. Giitsidis, E. G. Karakasis, A. Gasteratos, and G. C. Sirakoulis, “Human and fire detection from high altitude UAV images, ” in Proc. 23rd Euromicro Int. Conf. Parallel, Distributed, and Network-Based Processing, pp. 309–315, Mar. 2015.
    P.I. Pounds, D. Bersak, and A. Dollar, “Grasping from the air: Hovering capture and load stability, ” in Proc. IEEE Int. Conf. Robotics and Automation, pp. 2491–2498, May 2011.
    S. Sato, C. Premachandra, and K. Kato, “Position and attitude estimation using ultrasonic waves for autonomous aerial robots and system construction, ” in Proc. Control Automation and Systems, pp. 243–248, 2015.
    Chinthaka Premachandra, S. Takagi, and K. Kato, “Flying control of small-type helicopter by detecting its in-air natural features,” J. Electrical Systems and Information Technology(Elsevier), vol. 2, no. 1, pp. 58–74, May 2015. doi: 10.1016/j.jesit.2015.03.006
    M. Clark and R. C. Roberts, “Autonomous quadrotor terrain-following with a laser rangefinder and gimbal system, ” in Proc. IEEE SENSORS, Oct. 2017.
    M. S Arifin, Y. Y. Nazaruddin, T. A. Tamba, R. A. Santosa, and A. Widyotriatmo, “Experimental modeling of a quadrotor UAV using an indoor local positioning system, ” in Proc. 5th Int. Conf. Electric Vehicular Technology, pp. 25–30, 2018.
    K. Nakajima, Chinthaka Premachandra, and K. Kato, “3D environment mapping and self-position estimation by a small flying robot mounted with a movable ultrasonic range sensor,” J. Electrical Systems and Information Technology, vol. 4, no. 2, pp. 289–298, Sept. 2017. doi: 10.1016/j.jesit.2017.01.007
    D. Iwakura, K. Nonami, and D. Fujiwara, “A Study on localization and autonomous flight of aerial robot based on minimal IR sensors”, in Proc. JSME Conf. Robotics and Mechatronics, May 2012.
    C. Premachandra, D. Ueda, and K. Kato, “Speed-up automatic quadcopter position detection by sensing propeller rotation,” IEEE Sensors J., vol. 19, no. 7, pp. 2758–2766, Apr. 2019. doi: 10.1109/JSEN.2018.2888909
    Y. Kubota and Y. Iwatani, “Dependable takeoff and landing control of a small-scale helicopter with a wireless camera, ” in Proc. IEEE Int. Conf. Robotics and Biomimetics, pp.1279–1284, 2011.
    R. Mori, T. Kubo, and T. Kinoshita, “Vision-based hovering control of a small-scale unmanned helicopter, ” in Proc. SICE-ICASE Int. Joint Conf., pp. 1274–1278, 2006.
    C. Xu, L. Qiu, M. Liu, B. Kong, and Y. Ge, “Stereo vision based relative pose and motion estimation for unmanned helicopter landing”, in Proc. IEEE Int. Conf. Information Acquisition, pp. 31–36, Aug. 2006.
    T. Kudo, Y. Taguchi, M. Nitta, and K. Kato, “Positional estimation using natural features for autonomous helicopter”, in Proc. 53th Japan Joint Automatic Control Conf., Japan, pp. 1120–1123, Nov. 2010.
    T. Nemoto and U. M. Hirata, “Markerless autonomous control of a small RC helicopter using a vehicle-mounted camera”, in Proc. 53th Japan Joint Automatic Control Conf., pp. 1051–1054, Nov. 2010.
    G. Nakanishi, C. Premachandra, and K. Kato, “Improved method for horizontal movement measurement of small type helicopter using natural floor features”, in Proc. Joint Conf. IWAIT & IFMIA, Taiwan, China, Jan. 2015.
    C. Harris and M. Stephens, “A Combined Corner and Edge Detector”. in Proc. Alvey Vision Conf., 1988.
    L. Gueguen and M. Pesaresi, “Multi scale Harris corner detector based on differential morphological decomposition,” Pattern Recognition Letters, vol. 32, no. 14, pp. 1714–1719, Sept. 2011.
    J. L. Yin, B. H. Chen, and Y. Li, “Highly accurate image reconstruction for multimodal noise suppression using semisupervised learning on big data,” IEEE Trans. Multimedia, vol. 20, no. 2, pp. 3045–3056, 2018.
    N. H. Hai, D. N. H. Thanh, N. N. Hien, C. Premachandra, and S. Prasath, “A fast denoising algorithm for X-Ray images with variance stabilizing transform” in Proc. 11th IEEE Int. Conf. Knowledge and Systems Engineering, Oct. 2019.
    C. L. P. Chen, L. Liu, L. Chen, Y. Y. Tang, and Y. Zhou, “Weighted couple sparse representation with classified regularization for impulse noise removal,” IEEE Trans. Image Processing, vol. 24, no. 11, pp. 4014–4026, Nov. 2015. doi: 10.1109/TIP.2015.2456432
    U. Erkan, D. N. H. Thanh, L. M. Hieu, and S. Enginoglu, “An iterative mean filter for image denoising,” IEEE Access, vol. 7, pp. 167847–167859, 2019. doi: 10.1109/ACCESS.2019.2953924
    D. N. H. Thanh, L. T. Thanh, N. N. Hien, V. B. S. Prasath, “Adaptive total variation L1 regularization for salt and pepper image denoising,” Optik, vol. 208, 2020. doi: 10.1016/j.ijleo.2019.163677
    Z. Zhang and L. Zheng, “A complex varying-parameter convergent-differential neural-network for solving online time-varying complex sylvester equation,” IEEE Trans. Cybernetics, vol. 49, no. 10, pp. 3627–3639, 2018.
    C. Premachandra, R. Gohara, T. Ninomiya, and K. Kato, “Smooth automatic stopping system for ultra-compact vehicles,” IEEE Trans. Intelligent Vehicles, vol. 4, no. 4, pp. 561–568, Dec. 2019. doi: 10.1109/TIV.2019.2938098
    R. Gohara, C. Premachandra, and K. Kato, “A study on smooth automatic vehicle stopping control for suddenly-appeared obstacles, ” in Proc. IEEE Int. Conf. Vehicular Electronics and Safety, pp. 86–90, Nov. 2015.
    C. Premachandra, M. Otsuka, R. Gohara, T. Ninomiya, and K. Kato, “A study on development of a hybrid aerial/terrestrial robot system for avoiding ground obstacles by flight,” IEEE/CAA J. Autom. Sinica, vol. 6, no. 1, pp. 327–336, 2019. doi: 10.1109/JAS.2018.7511258
    T. Luukkonen, “Modelling and control of quadcopter,” Independent Research Project in Applied Mathematics of School of Science, Aalto University, Aug. 2011.


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    • 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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