Design and Implementation of Moving Object Visual Tracking System using μ-Synthesis Controller
Considering the increasing use of security and surveillance systems, moving object tracking systems are an interesting research topic in the field of computer vision. In general, a moving object tracking system consists of two integrated parts, namely the video tracking part that predicts the position of the target in the image plane, and the visual servo part that controls the movement of the camera following the movement of objects in the image plane. For tracking purposes, the camera is used as a visual sensor and applied to a 2-DOF (yaw-pitch) manipulator platform with an eye-in-hand camera configuration. Although its operation is relatively simple, the yaw-pitch camera platform still needs a good control method to improve its performance. In this study, we propose a moving object tracking system on a prototype yaw-pitch platform. A m-synthesis controller was used to control the movement of the visual servo part and keep the target in the center of the image plane. The experimental results showed relatively good results from the proposed system to work in real-time conditions with high tracking accuracy in both indoor and outdoor environments.
Castelli, F., Michieletto, S., Ghidoni, S. & Pagello, E., A Machine Learning-based Visual Servoing Approach for Fast Robot Control in Industrial Setting, International Journal of Advanced Robotic System, 14(6), pp. 1-10, Nov. 2017.
Burlion, L., Plinval, H. de & Mouyon, P., Backstepping Based Visual Servoing for Transport Aircraft Automatic Landing, 2014 IEEE Conference on Control Applications (CCA), pp. 1461-1466, 2014.
Mathiassen, K., Glette, K. & Elle, O.J., Visual Servoing of a Medical Ultrasound Probe for Needle Insertion, 2016 IEEE International Conference on Robotics and Automation (ICRA), pp. 3426-3433, 2016.
Aygun, M.T., MacKunis, W. & Mehta, S., Robust Image-based Visual Servo Control of an Uncertain Missile Airframe, IFAC Proceedings Volumes, 47(3), pp. 5085-5090, 2014.
Mendez, M.A.O., Fu, C., Ludivig, P., Bissyandé, T.F., Kannan, S., Zurad, M., Annaiyan, A., Voos, H. & Campoy, P., Towards an Autonomous Vision-based Unmanned Aerial System Against Wildlife Poachers, Sensors, 15(12), pp. 31362-31391, Dec. 2015.
Nugroho, T.H., Mangkusamisto, F., Trilaksono, B.R., Indriyanto, T. & Yulianti, L., Enhancing Color-Based Particle Filter Algorithm with ORB Feature for Real-Time Video Tracking, 2018 IEEE International Conference on Signal and Systems (IcSigSys), pp. 53-58, 2018.
Redmon, J., Divvala, S., Girshick, R. & Farhadi, A., You Only Look Once: Unified, Real-Time Object Detection, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 779-788, 2016.
Yuan, L., Qu, Z., Zhao, Y., Zhang, H. & Nian, Q., A Convolutional Neural Network Based on Tensorflow for Face Recognition, 2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), pp. 525-529, 2017.
Hare, S., Saffari, A. & Torr, P.H.S., Struck: Structured Output Tracking with Kernels, 2011 IEEE International Conference on Computer Vision (ICCV), pp. 263-270, 2011.
Santamaria-Navarro, A. & Andrade-Cetto, J., Uncalibrated Image-Based Visual Servoing, 2013 IEEE International Conference on Robotics and Automation (ICRA), pp. 5247-5252, 2013.
Cindy, X., Collange, F., Jurie, F. & Martinet, P., Object Tracking with A Pan-Tilt-Zoom Camera: Application to Car Driving Assistance, 2001 IEEE International Conference on Robotics and Automation (ICRA), pp. 1653-1658, 2001.
Naik, C., Malu, S.K. & Majumdar, J., Image Based Visual Servoing with Linear Quadratic Regulator Control for Mobile Robot, International Journal of Applied Engineering Research, 9(11), pp. 1359-1372, 2014.
Mangkusasmito, F., Nugroho, T.H., Trilaksono, B.R. & Indriyanto, T., Visual Servo Strategies Using Linear Quadratic Gaussian (LQG) for Yaw-Pitch Camera Platform, 2018 International Conference on Signals and Systems (ICSigSys), pp. 146-150, 2018.
Zhou, K. & Doyle, J.C., Essentials of Robust Control, Prentice Hall, 1999.
Hare, S., Golodetz, S., Saffari, A., Vineet, V., Cheng, M.M., Hicks, S.L. & Torr, P.H.S., Struck: Structured Output Tracking with Kernels, IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(10), pp. 2096-2109, Oct. 2016.
Yahya, M.F. & Arshad, M.R., Image-Based Visual Servoing for Docking of an Autonomous Underwater Vehicle, 2018 IEEE 7th International Conference on Signals Underwater System Technology: Theory and Applications (USYS), pp. 54-59, 2017.
- There are currently no refbacks.
ITB Journal Publisher, LPPM – ITB,
Center for Research and Community Services (CRCS) Building Floor 7th,
Jl. Ganesha No. 10 Bandung 40132, Indonesia,