CNN for IMU Assisted Odometry Estimation using Velodyne LiDAR

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F18%3APU132246" target="_blank" >RIV/00216305:26230/18:PU132246 - isvavai.cz</a>
Result on the web
<a href="http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8374163&isnumber=8374143" target="_blank" >http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8374163&isnumber=8374143</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICARSC.2018.8374163" target="_blank" >10.1109/ICARSC.2018.8374163</a>

Result language
angličtina
Original language name
CNN for IMU Assisted Odometry Estimation using Velodyne LiDAR
Original language description
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.
Czech name
—
Czech description
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
IEEE International Conference on Autonomous Robot Systems and Competitions
ISBN
978-1-5386-5221-3
ISSN
2573-9387
e-ISSN
—
Number of pages
7
Pages from-to
71-77
Publisher name
Institute of Electrical and Electronics Engineers
Place of publication
Torres Vedras
Event location
Torres Vedras
Event date
Apr 25, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000435384800014

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