Fiducial Markers Aided Position Estimation for Vertical Landing

Main Article Content

Recep Behlül Şahin
Muharrem Mercimek


Autonomous landing is a critical step in unmanned aerial vehicles (UAVs) and requires accurate position information. In cases where GPS signals are unavailable or obstructed, vision-based approaches can provide support for landing capabilities. In this study, a vision-based position estimation algorithm is being developed in conjunction with markers used in vertical take-off and landing (VTOL) systems of UAVs. The developed framework is designed to be compatible with various types of visual markers. The Kalman Filter is used to the calculated position to correct measurement errors and reduce the uncertainty of the position estimation. The developed algorithm is extensively tested in a simulation environment. The positions of a quadrotor aircraft are compared with real measurements to analyze the performance of the proposed vision-based position estimation algorithm. The results demonstrate an acceptable level of accuracy for the algorithm. This study discusses the potential of using visual markers and integrating Kalman filtering to improve the accuracy of positioning in vertical takeoff and landing systems of the UAVs. The development of a vision-based position estimation algorithm can enhance the reliability and precision of autonomous landing capabilities and enable successful landings in situations where GPS signals are limited or unavailable.


Download data is not yet available.

Article Details

How to Cite
Şahin, R. B., & Mercimek, M. (2023). Fiducial Markers Aided Position Estimation for Vertical Landing. The European Journal of Research and Development, 3(2), 29–45.


Ariyur K B, Fregene K O. Autonomous tracking of a ground vehicle by a UAV[C] American Control Conference. 2008. DOI:

Iwakura, D.; Wang, W.; Nonami, K.; Haley, M. Movable Range-Finding Sensor System and Pre-cise Automated Landing of Quad-Rotor MAV. J. Syst. Des. Dyn. 2011, 5, 17–29. DOI:

Gautam A, Singh M, Sujit PB, Saripalli S. Autonomous Quadcopter Landing on a Moving Target. Sensors. 2022; 22(3):1116.

Arora, S.; Jain, S.; Scherer, S.; Nuske, S.; Chamberlain, L.; Singh, S. Infrastructure-free shipdeck tracking for autonomous landing. In Pro-ceedings of the IEEE International Conference on Robotics and

Auto-mation,Karlsruhe, Germany, 6–10 May 2013; pp. 323–330. Gautam A, Singh M, Sujit PB, Saripalli S. Autonomous Quadcopter Landing on a Moving Target. Sensors. 2022; 22(3):1116. DOI:

Herissé, B.; Hamel, T.; Mahony, R.; Russotto, F.X. Landing a VTOL Unmanned Aerial Vehicle on a Moving Platform Using Optical Flow. IEEE Trans. Robot. 2012, 28, 77–89. DOI:

M. UZUNOGLU, R. B. ŞAHİN and M. MERCİMEK, "Vision-Based Position Estimation with Mark-ers For Quadrotors," 2022 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA), Ankara, Turkey, 2022, pp. 1-6, doi: 10.1109/HORA55278.2022. 9800043. DOI:

Zhang, Zhuming & Hu, Yongtao & Yu, Guoxing & Dai, Jingwen. (2021). DeepTag: A General Framework for Fiducial Marker Design and Detection. DOI:

Ozuag, Ersin & Erturk, Sarp. (2014). A Homography Matrix Decomposition Based Video Synchro-nization Approach. 2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 - Proceedings. 10.1109/SIU.2014.6830661. DOI:

V. Klema and A. Laub, "The singular value decomposition: Its computation and some applica-tions," in IEEE Transactions on Automatic Control, vol. 25, no. 2, pp. 164-176, April 1980. DOI:

Y. Ito and Y. Oda, "Estimation of Camera Projection Matrix Using Linear Matrix Inequalities," 2016 Joint 8th International Conference on Soft Computing and Intelligent Systems (SCIS) and 17th Interna-tional Symposium on Advanced Intelligent Systems (ISIS), 2016, pp. 72-75. DOI:

Charles K. Chui and Guanrong Chen. 2017. Kalman Filtering: With Real-Time Applications (5th ed.). Springer Publishing Company, Incor- porated.

Stanford Artificial Intelligence Laboratory et al. (2018). Robotic Operating System. Retrieved from

N. Koenig and A. Howard, "Design and use paradigms for Gazebo, an open-source multi-robot simulator," 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566), Sendai, Japan, 2004, pp. 2149-2154 vol.3, doi: 10.1109/IROS.2004.1389727. DOI:

"ArduPilot", ArduPilot Documentation - ArduPilot documentation, [online] Available: