Object Detection on Images in Docking Tasks Using Deep Neural Networks

  • Ivan FominEmail author
  • Dmitrii Gromoshinskii
  • Aleksandr Bakhshiev
Conference paper
Part of the Studies in Computational Intelligence book series (SCI, volume 736)


In process of docking of automated apparatus there is a problem of determining of them relative position. This problem may be effectively solved with algorithms for relative position calculation, based on television picture formed by camera, installed on one apparatus and observing another one, or docking position. Apparatus position and orientation calculates using visual landmarks positions and information about 3D configuration of observing object and visual landmarks’ relative positions. Visual landmarks detection algorithm is the crucial part of such solution. Study of ability of application of object detection system based on deep convolutional neural network to task of visual landmark detection will be discussed in this article. As an example, detection of visual landmarks on space docking images will be discussed. Neural network based detection system learned using images of International Space Station received in process of docking of cargo spacecrafts will be represented.


Object detection Deep neural networks Convolutional neural networks Faster R-CNN Machine learning Computer vision 


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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Ivan Fomin
    • 1
    Email author
  • Dmitrii Gromoshinskii
    • 1
  • Aleksandr Bakhshiev
    • 1
  1. 1.The Russian State Scientific Center for Robotics and Technical Cybernetics (RTC)Saint-PetersburgRussia

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