Position based visual servoing with artificial neural networks for quadrotor-type unmanned aerial vehicles Dört kanatli insansiz hava araçlari için yapay sinir aǧlari ile konum tabanli görsel servolama

Unlu A., YÜKSEL T.

29th IEEE Conference on Signal Processing and Communications Applications, SIU 2021, Virtual, Istanbul, Turkey, 9 - 11 June 2021, (Full Text) identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/siu53274.2021.9477912
  • City: Virtual, Istanbul
  • Country: Turkey
  • Keywords: Artificial neural networks, Position based visual servoing, Quadrotor-type Unmanned Aerial Vehicles
  • Bilecik Şeyh Edebali University Affiliated: Yes

Abstract

© 2021 IEEE.UAVs offer many advantages over manned vehicles and their application area expands in time passes. Particularly, interest in UAVs with rotary wing types is increasing. Increasing interest in these vehicles has spawned many different controller designs. In this study, estimating the pose of the vehicle according to the image features with the help of a single camera mounted on the quadrotor and then positionbased visual servoing, a technique that allows the vehicle to be controlled by using the image features, was used. In this study position-based visual servoing (PBVS); 3D parameter estimates of the vehicle pose were implemented with artificial neural networks.