Online visual robot tracking and identification using deep LSTM networks

@article{Farazi2017OnlineVR,
  title={Online visual robot tracking and identification using deep LSTM networks},
  author={Hafez Farazi and Sven Behnke},
  journal={2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  year={2017},
  pages={6118-6125}
}
  • Hafez Farazi, Sven Behnke
  • Published in
    IEEE/RSJ International…
    2017
  • Engineering, Computer Science
  • Collaborative robots working on a common task are necessary for many applications. One of the challenges for achieving collaboration in a team of robots is mutual tracking and identification. We present a novel pipeline for online vision-based detection, tracking and identification of robots with a known and identical appearance. Our method runs in realtime on the limited hardware of the observer robot. Unlike previous works addressing robot tracking and identification, we use a data-driven… CONTINUE READING

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