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

Chinthaka Premachandra; Dang Ngoc Hoang Thanh; Tomotaka Kimura; Hiroharu Kawanaka

doi:10.1109/JAS.2020.1003240

Volume 7 Issue 4

Jun. 2020

IEEE/CAA Journal of Automatica Sinica

JCR Impact Factor: 11.8, Top 4% (SCI Q1)

CiteScore: 17.6, Top 3% (Q1)
Google Scholar h5-index: 77， TOP 5

Turn off MathJax

Article Contents

Article Navigation > IEEE/CAA Journal of Automatica Sinica > 2020 > 7(4): 1016-1025

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

Citation:

PDF( 1564 KB)

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)

More Information

Author Bio:
Chinthaka Premachandra (M’11) received the B.Sc. and M.Sc. degrees from Mie University, Japan, in 2006 and 2008, respectively, and the Ph.D degree from the Nagoya University, Japan, in 2011. From 2012 to 2015, Dr. Chinthaka Premachandra was an Assistant Professor in the Department of Electrical Engineering, Faculty of Engineering, Tokyo University of Science, Japan. From 2016 to 2017, he was an Assistant in the Department of Electronic Engineering, School of Engineering, Shibaura Institute of Technology, Japan. In 2018, he was promoted to Associate Professor in the Department of Electronic Engineering, Graduate School of Engineering, Shibaura Institute of Technology. In addition, he is the Manager of Image Processing and Robotic Lab at the same department. His lab conducts research in two main fields: image processing and robotics. Former research includes computer vision, pattern recognition, speed up image processing, and camera based intelligent transportation systems, while latter fields include terrestrial robotic systems, flying robotic systems, and integration of terrestrial robot and flying robot.He received the FIT Best Paper Award and FIT Young Researchers Award from IEICE & IPSJ, Japan in 2009 and 2010, respectively. He has served many international conferences and journals as a Steering Committee Member and an Editor, respectively. He is the Founding Chair of International Conference on Image Processing and Robotics (ICIPRoB). He is the member of IEEE, IEICE (Japan), SICE (Japan) and SOFT (Japan)

Dang Ngoc Hoang Thanh received the bachelor degree and the M.Sc. degree in applied mathematics from Belarusian State University, Belarus, in 2008 and 2009, respectively, and the Ph.D. degree in computer science from Tula State University, Russia, in 2016.He was a Lecturer with the Department of Information Technology, Hue College of Industry, Vietnam. He is currently an Assistant Professor with the Department of Information Technology, School of Business Information Technology, University of Economics Ho Chi Minh City, Vietnam. He has more than 50 works on international peer-reviewed journals and conference proceedings, 5 book chapters, 1 book, and 1 European Patent. His research interests include image processing, computer vision, machine learning, data classification, computational mathematics, fuzzy mathematics, and optimization. He is a Member of Scientific Organization INSTICC, ACM, and IAENG. He is also a Member of international conferences committee, such as the IEEE ICCE 2018,Vietnam, IWBBIO, Spain, the IEEE ICIEV, USA, the IEEE ICEEE, Turkey, ICIEE, Japan, ICoCTA, Australia, and ICMTEL, U.K

Tomotaka Kimura (M’09) is currently an Associate Professor in the Department of Intelligent Information Engineering, Faculty of Science and Engineering, Doshisha University, Japan. He received the B.Eng., M.Eng., and Ph.D. degrees in communications engineering from Osaka University, Japan, in 2008, 2010, 2015, respectively. From April 2015 to March 2018, he was an Assistant Professor in the Department of Electrical Engineering, Faculty of Engineering, Tokyo University of Science, Japan. From April 2018 to March 2020, he was an Assistant Professor in the Department of Intelligent Information Engineering, Faculty of Science and Engineering, Doshisha University. His research interests include performance analysis of communication networks and image processing. He received the IEICE Young Researchers’ Award in 2016. He is a Member of IEEE, IEICE, IEEJ, and JSAI

Hiroharu Kawanaka (M’07) was graduated from Faculty of Engineering at Mie University, Japan, in 1999 and received Dr. of Eng. from Mie University Graduate School of Engineering, Japan, in 2004. After the graduation, he again entered Mie University Graduate School of Medicine to study medical informatics and medical information systems. In 2004, he established a company for medical information systems “Medical Engineering Institute, Inc.” The company develops “CLISTA!,” which is a DataWareHouse for clinical use. Currently, more than 100 large-scale hospitals use the system to analyze clinical data archived in the EHR for clinical studies or business analyses. He is one of the Founders of this company and also a Director of the company from 2004. From 2006, he joined in Graduate School of Engineering, Mie University as an Assistant Professor. He received the Ph. D. degree in medical science (D.M.Sc) from Mie University Graduate School of Medicine in 2009. From 2017, he is an Associate Professor at Graduate School of Engineering, Mie University. Also, he has been invited as a Visiting Associate Professor at Suzuka University of Medical Science, Japan. In 2005, he received a grant “NEDO*1 Industry Fellowship Program” and worked for Mie Technical License Organization (Mie TLO) to support research collaborations, venture companies. His current research interests include medical informatics, medical document image analysis, graphics recognition, welfare information systems, ergonomics, evolutionary computations and its application. He is a Member of IEEE (and SMC Society), HIMSS and some Japanese academic societies
Corresponding author: C. Premachandra is with the Department of Electronic Engineering and Science, Graduate School of Engineering, Shibaura Institute of Technology, Tokyo 135-8548, Japan (e-mail: chintaka@sic.shibaura-it.ac.jp)
Received Date: 2020-03-18
Accepted Date: 2020-04-13

Available Online: 2020-05-15

Abstract

Abstract

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.
- Hovering control,
- light weight algorithm development,
- image processing,
- self-position estimation,
- small aerial robot,
- tile corner sensing

FullText(HTML)

References(33)

References

[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.
[2]	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.
[3]	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.
[4]	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
[5]	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.
[6]	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.
[7]	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.
[8]	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.
[9]	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.
[10]	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
[11]	M. Clark and R. C. Roberts, “Autonomous quadrotor terrain-following with a laser rangefinder and gimbal system, ” in Proc. IEEE SENSORS, Oct. 2017.
[12]	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.
[13]	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
[14]	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.
[15]	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
[16]	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.
[17]	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.
[18]	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.
[19]	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.
[20]	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.
[21]	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.
[22]	C. Harris and M. Stephens, “A Combined Corner and Edge Detector”. in Proc. Alvey Vision Conf., 1988.
[23]	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.
[24]	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.
[25]	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.
[26]	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
[27]	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
[28]	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
[29]	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.
[30]	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
[31]	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.
[32]	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
[33]	T. Luukkonen, “Modelling and control of quadcopter,” Independent Research Project in Applied Mathematics of School of Science, Aalto University, Aug. 2011.

Supplements(0)

Cited By

Proportional views

Proportional views

通讯作者: 陈斌, bchen63@163.com

1.
沈阳化工大学材料科学与工程学院沈阳 110142

Figures(28)

Get Citation

PDF

XML

Article Metrics

Article views (1191) PDF downloads(96)

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.

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

doi: 10.1109/JAS.2020.1003240

Abstract

References

Proportional views

Catalog

通讯作者: 陈斌, bchen63@163.com

Article Metrics

Highlights

Export File

Citation

Format

Content