Control of Quadrotors Using Neural Networks for Precise Landing Maneuvers

  • U. S. Ananthakrishnan
  • Nagarajan Akshay
  • Gayathri Manikutty
  • Rao R. Bhavani
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 517)

Abstract

Aerial and ground robots have been widely used in tandem to overcome the limitations of the individual systems, such as short run time and limited field of view. Several strategies have been proposed for this collaboration and all of them involve periodic autonomous precision landing of the aerial vehicle on the ground robot for recharging. Intelligent control systems like neural networks lend themselves naturally to precision landing applications since they offer immunity to system dynamics and adaptability to various environments. Our work describes an offline neural network backpropagation controller to provide visual servoing for the landing operation. The quadrotor control system is designed to perform precise landing on a marker platform within the specified time and distance constraints. The proposed method has been simulated and validated in a Gazebo and robot operating system simulation environment.

Keywords

UAV-UGV collaboration Quadrotor landing Vision based navigation Neural networks Backpropagation algorithm ROS architecture 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2017

Authors and Affiliations

  • U. S. Ananthakrishnan
    • 1
  • Nagarajan Akshay
    • 1
  • Gayathri Manikutty
    • 1
  • Rao R. Bhavani
    • 1
  1. 1.AMMACHI LabsAmrita School of Engineering, Amritapuri Amrita Vishwa Vidyapeetham Amrita UniversityKollamIndia

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