Abstract
The automated operation of Unmanned Aerial Vehicles (UAVs) has become increasingly important, and one key step in the procedure is the accurate landing of such vehicles. A major problem is that when trying to design a control algorithm for the landing procedure, it is difficult to accurately measure the 3D pose of the vehicle with respect to the local environment. Three dimensional pose estimation and subsequent corrections in velocity to design the control system was omitted by using an image-based visual servoing controller. Another important development is choosing the appropriate visual features which ensures convergence to desired position. The proposed controller with image moments as features was able to converge and land the vehicle accurately using only the image moments as the visual features from two fiducial markers without any local position or global position information. The proposed method has been verified using simulations considering an existing model of UAV.
Riby Abraham Boby and Alexandr Klimchik were supported by RSF research grant No. 22-41-02006.
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Hegazy, M., Boby, R.A., Klimchik, A. (2024). Localization of a Drone for Landing Using Image-Based Visual Servoing with Image Moments. In: Ghoshal, S.K., Samantaray, A.K., Bandyopadhyay, S. (eds) Recent Advances in Industrial Machines and Mechanisms. IPROMM 2022. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-99-4270-1_13
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