AI-Based Visual Odometry Implementation on an Embedded System

Büyüksolak O., Güneş E. O.

10th International Conference on Electrical and Electronics Engineering, ICEEE 2023, İstanbul, Türkiye, 8 - 10 Mayıs 2023, ss.47-51 identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/iceee59925.2023.00016
  • Basıldığı Şehir: İstanbul
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.47-51
  • Anahtar Kelimeler: CNN, Deep Learning, Embedded System, KITTI, Visual Odometry
  • İstanbul Teknik Üniversitesi Adresli: Evet

Özet

Embedded visual odometry(VO) implementation may provide a low-power, small-size alternative or compan-ion positioning system to the Global Navigation Satellite Systems(GNSS) and Inertial Navigation System(INS). As the em-bedded systems are memory scarce, in this paper, a new low-memory footprint neural network-based visual odometry method that is implementable on embedded systems is introduced and evaluated. To deploy the neural network, MAX78002 [1] artificial intelligence microcontroller has been chosen as the embedded platform. To the best of our knowledge, this is the first study that provides a microcontroller-based visual odometry solution.