Publication Details

CNN for IMU Assisted Odometry Estimation using Velodyne LiDAR

VEĽAS Martin, ŠPANĚL Michal, HRADIŠ Michal and HEROUT Adam. CNN for IMU Assisted Odometry Estimation using Velodyne LiDAR. In: Proceedings of IEEE International Conference on Autonomous Robot Systems and Competitions. Torres Vedras: Institute of Electrical and Electronics Engineers, 2018, pp. 71-77. ISBN 978-1-5386-5221-3. Available from: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8374163&isnumber=8374143
Czech title
Konvoluční sítě pro odhad odometrie v datech LiDARu Velodyne za pomoci IMU senzoru
Type
conference paper
Language
english
Authors
URL
Keywords
ground segmentation, LiDAR, Velodyne, convolutional neural network
Abstract
We introduce a novel method for odometry estimation using convolutional neural networks from 3D LiDAR scans. The original sparse data are encoded into 2D matrices for the training of proposed networks and for the prediction. Our networks show significantly better precision in the estimation of translational motion parameters comparing with state of the art method LOAM, while achieving real-time performance. Together with IMU support, high quality odometry estimation and LiDAR data registration is realized. Moreover, we propose alternative CNNs trained for the prediction of rotational motion parameters while achieving results also comparable with state of the art. The proposed method can replace wheel encoders in odometry estimation or supplement missing GPS data, when the GNSS signal absents (e.g. during the indoor mapping). Our solution brings real-time performance and precision which are useful to provide online preview of the mapping results and verification of the map completeness in real time.
Published
2018
Pages
71-77
Proceedings
Proceedings of IEEE International Conference on Autonomous Robot Systems and Competitions
Conference
IEEE International Conference on Autonomous Robot Systems and Competitions, Torres Vedras, PT
ISBN
978-1-5386-5221-3
Publisher
Institute of Electrical and Electronics Engineers
Place
Torres Vedras, PT
DOI
BibTeX
@INPROCEEDINGS{FITPUB11527,
   author = "Martin Ve\'{l}as and Michal \v{S}pan\v{e}l and Michal Hradi\v{s} and Adam Herout",
   title = "CNN for IMU Assisted Odometry Estimation using Velodyne LiDAR",
   pages = "71--77",
   booktitle = "Proceedings of IEEE International Conference on Autonomous Robot Systems and Competitions",
   year = 2018,
   location = "Torres Vedras, PT",
   publisher = "Institute of Electrical and Electronics Engineers",
   ISBN = "978-1-5386-5221-3",
   doi = "10.1109/ICARSC.2018.8374163",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/11527"
}
Back to top