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cs.RO2017
CNN for IMU Assisted Odometry Estimation using Velodyne LiDAR
Martin Velas, Michal Spanel, Michal Hradis +1
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…
cs.RO2017
CNN for Very Fast Ground Segmentation in Velodyne LiDAR Data
Martin Velas, Michal Spanel, Michal Hradis +1
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 convo…