A Nonlinear Camera Gimbal Visual Servoing Control using Command Filtered Backstepping

Fadjar Rahino Triputra, Bambang Riyanto Trilaksono, Trio Adiono, Rianto Adhy Sasongko, Mohamad Dahsyat


This paper presents a method for modeling both the motion of a target feature in a camera sensor plane of images and the movement of a pan-tilt gimbal mechanism that is usually mounted on a fixed-wing unmanned aerial vehicle (UAV). The target features can be obtained from a common method of a feature extraction. Here, we utilize an image extraction method of Tracking, Learning, and Detection (TLD) that have a prominent long-term tracking. Futhermore, we employ an image base visual servoing (IBVS) control method to direct the camera always pointing at an object target in a distance using the pan-tilt gimbal mechanism while the fixed-wing UAV cruising above. Our works are modeling a nonlinear camera gimbal movement and designing a nonlinear adaptive control of command filtered backstepping (CFBS) to make a solution for the nonlinear IBVS control problem that have complicated movements of the image features and the gimbal pan-tilt mechanism in despite of the radical movements of the UAV itself. We also show that the CFBS design is easier than integral backstepping (IBS) because no requirement of model derivation procedure. Software and hardware in the loop simulation (SILS / HILS) results show the stability of the control of IBVS using CFBS.


image based visual servoing; command filtered backstepping; nonlinear camera gimbal modeling

Full Text:



Z. Kalal, K. Mikolajczyk, and J. Matas, “Tracking-learning-detection,” Pattern Analysis and Machine Intelligence, vol. 34, no. 7, pp. 1409–1422, July 2012. https://doi.org/10.1109/TPAMI.2011.239

S. Hutchinson, G. Hager, and P. Cork, "A tutorial on visual servo control," IEEE Transactions on Robotics Automation, vol. 12, no. 5, pp. 651-670, Oct. 1996.

F. Chaumette and S. Hutchinson, "Visual servo control, part I: basic approaches," IEEE Robotics and Automation Magazine, vol. 13, no. 4, pp. 82-90, 2006.

F. Chaumette and S. Hutchinson, "Visual servo control, part II: advanced approaches," IEEE Robotics and Automation Magazine, vol. 14, no. 1, pp. 109-118, 2007.

T. Hamel and R. Mahony, "Visual servoing of an under-actuated dynamic rigid-body system: An image-based approach," IEEE Transactions on Robotics Automation, vol. 18, no. 2, pp. 187-198, 2002.

O. Bourquardez, R. Mahony, N. Guenard, F. Chaumette, T. Hamel, and L. Eek, "Image-based visual servo control of the translation kinematics of a quadrotor aerial vehicle," IEEE Transactions on Robotics, vol. 25, no. 3, pp. 743-749, June 2009.

F. Le Bras, T. Hamel, C. Barat, and R. Mahony, "Image-based visual servo controller for automatic landing guidance of a fixed-wing aircraft," IEEE European Control Conference, pp. 1836-1841, Aug. 23-26, 2009.

F. Le Bras, T. Hamel, and R. Mahony, "Image-based visual servo control for circular trajectories for a fixed-wing aircraft," Proceeding of the 48th IEEE Conf. on Decision and Control, pp. 3430 - 3435, Dec. 15-18, 2009.

P. Peliti, L. Rosa, G. Oriolo, and M. Vendittelli, “Vision-based loitering over a target for a fixed-wing UAV,” Proc. of IFAC Sym. on Robot Control, pp. 51-57, 2012.

Hasan K. Khalil, Nonlinear Systems. New Jersey: Prentice Hall, 2002.

Miroslav Krstic, Ioannis Kanellakopoulos, and Petar Kokotovic, Nonlinear and Adaptive Control Design. New York: John Willey & Sons, 1995.

Jay A. Farrell and Marios M. Polycarpou, Adaptive Approximation Based Control. New York: John Willey & Sons, 2006.

Jay A. Farrel, M. M. Polycarpou, and M. Sharma, "Command Filtered Backstepping," IEEE Transaction on Automatic Control, vol. 54, no. 6, pp. 1391-1395, June 2009.

Peter Corke, Robotics, Vision and Control: Fundamental Algorithms in MATLAB. Berlin Heidelberg: Springer Publishing, 2013.

Georg Nebehay, Branislav Micusik, Cristina Picus, and Roman Pflugfelder, Evaluation of an online learning approach for robust object tracking. Technical Report AIT-DSS-TR-0279, AIT Austrian Institute of Technology, 2011.


Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.