@inproceedings{ahmadi2020icra,
  abstract     = {Autonomous navigation is a pre-requisite for fieldrobots  to  carry  out  precision  agriculture  tasks.  Typically,  arobot has to navigate through a whole crop field several timesduring  a  season  for  monitoring  the  plants,  for  applying  agro-chemicals,  or  for  performing  targeted  intervention  actions.  Inthis  paper,  we  propose  a  framework  tailored  for  navigation  inrow-crop  fields  by  exploiting  the  regular  crop-row  structurepresent in the fields. Our approach uses only the images fromon-board  cameras  without  the  need  for  performing  explicitlocalization  or  maintaining  a  map  of  the  field  and  thus  canoperate  without  expensive  RTK-GPS  solutions  often  used  inagriculture  automation  systems.  Our  navigation  approach  al-lows  the  robot  to  follow  the  crop-rows  accurately  and  handlesthe  switch  to  the  next  row  seamlessly  within  the  same  frame-work. We implemented our approach using C++ and ROS andthoroughly  tested  it  in  several  simulated  environments  withdifferent  shapes  and  sizes  of  field.  We  also  demonstrated  thesystem running at frame-rate on an actual robot operating ona  test  row-crop  field.  The  code  and  data  have  been  published.},
  videourl     = {https://youtu.be/0qg6n4sshHk},
  codeurl      = {https://github.com/PRBonn/visual-crop-row-navigation},
  url          = {proceedings: ahmadi2020icra.pdf},
  year         = {2020},
  pages        = {4920-4926},
  booktitle    = {Proc.~of the IEEE Intl.~Conf.~on Robotics & Automation (ICRA)},
  author       = {Ahmadi, A. and Nardi, L. and Chebrolu, N. and Stachniss, C.},
  title        = {Visual Servoing-based Navigation for Monitoring Row-Crop Fields},
}