On the Importance of the RGB-D Sensor Model in the CNN-based Robotic Perception
Ładowanie...
Data
2023
Autorzy
Tytuł czasopisma
ISSN czasopisma
Tytuł tomu
Wydawca
Wydawnictwo Politechniki Łódzkiej
Lodz University of Technology Press
Lodz University of Technology Press
Abstrakt
Mobile and manipulation robots operating indoors use RGB-D
cameras as the environment perception sensors. To process data from RGB
and depth cameras neural networks are applied. These neural-based systems
are trained using synthetic datasets due to the difficulties of obtaining ground
truth data on real robots. As a result, the neural model used on the real robot
does not produce satisfactory performance due to the differences between the
images used during training and the inference. In this paper, we show the
importance of depth sensor modeling while training the neural network on
a synthetic dataset. We show that the obtained neural model can be used on
the real robot and process the data from the real RGB-D camera.
Opis
Słowa kluczowe
robotics, RGB-D camera, neural perception, robotyka, kamera RGB-D, percepcja neuronowa
Cytowanie
Zieliński M., Belter D., On the Importance of the RGB-D Sensor Model in the CNN-based Robotic Perception. W: Progress in Polish Artificial Intelligence Research 4, Wojciechowski A. (Ed.), Lipiński P. (Ed.)., Seria: Monografie Politechniki Łódzkiej Nr. 2437, Wydawnictwo Politechniki Łódzkiej, Łódź 2023, s. 495-499, ISBN 978-83-66741-92-8, doi: 10.34658/9788366741928.79.