Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Martin Velas"'
Publikováno v:
Sensors, Vol 19, Iss 18, p 3944 (2019)
This paper presents a human-carried mapping backpack based on a pair of Velodyne LiDAR scanners. Our system is a universal solution for both large scale outdoor and smaller indoor environments. It benefits from a combination of two LiDAR scanners, wh
Externí odkaz:
https://doaj.org/article/28246a7ce31d46339c25159f2e960c47
Publikováno v:
ICARSC
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 signifi
Publikováno v:
ICARSC
This paper presents a novel method for ground segmentation in Velodyne point clouds. We propose an encoding of sparse 3D data from the Velodyne sensor suitable for training a convolutional neural network (CNN). This general purpose approach is used f
Publikováno v:
SENSORS. 2019, vol. 19, issue 18, p. 1-34.
Sensors (Basel, Switzerland)
Sensors, Vol 19, Iss 18, p 3944 (2019)
Sensors
Volume 19
Issue 18
Sensors (Basel, Switzerland)
Sensors, Vol 19, Iss 18, p 3944 (2019)
Sensors
Volume 19
Issue 18
This paper presents a human-carried mapping backpack based on a pair of Velodyne LiDAR scanners. Our system is a universal solution both for large scale outdoor and also smaller indoor environments. It benefits from a combination of two LiDAR scanner
Publikováno v:
SSCI
This paper proposes the use of change detection in a multi-view object recognition system in order to improve its flexibility and effectiveness in dynamic environments. Multi-view recognition approaches are essential to overcome problems related to c
Publikováno v:
ICRA
We present a novel way of odometry estimation from Velodyne LiDAR point cloud scans. The aim of our work is to overcome the most painful issues of Velodyne data - the sparsity and the quantity of data points - in an efficient way, enabling more preci
Publikováno v:
ACM Transactions on Embedded Computing Systems; Jan2024, Vol. 23 Issue 1, p1-26, 26p
Publikováno v:
Sensors (14248220). Feb2022, Vol. 22 Issue 3, p1052. 1p.
Publikováno v:
2016 IEEE International Conference on Robotics & Automation (ICRA); 2016, p4486-4495, 10p
Autor:
Velas, Martin1 (AUTHOR) ivelas@fit.vutbr.cz, Spanel, Michal1 (AUTHOR), Sleziak, Tomas2 (AUTHOR), Habrovec, Jiri2 (AUTHOR), Herout, Adam1 (AUTHOR)
Publikováno v:
Sensors (14248220). Sep2019, Vol. 19 Issue 18, p3944-3944. 1p.