loading page

LiDAR Odometry by Deep Learning-based Feature Points with Two-step Pose Estimation
  • +3
  • Tianyi Liu ,
  • Yan Wang ,
  • xiaoji niu ,
  • Chang Le ,
  • Tisheng Zhang ,
  • Jingnan Liu
Tianyi Liu
Wuhan University

Corresponding Author:[email protected]

Author Profile
xiaoji niu
Author Profile
Tisheng Zhang
Author Profile
Jingnan Liu
Author Profile

Abstract

KITTI dataset is collected from three types of environments, i.e., country, urban and highway The types of feature point cover a variety of scenes. The KITTI dataset provides 22 sequences of LiDAR data. 11 sequences of them from sequence 00 to sequence 10 are “training” data. The training data are provided with ground truth translation and rotation. In addition, field experiment data is collected by low-resolution LiDAR, VLP-16 in Wuhan Research and Innovation Center.
09 Jun 2022Published in Remote Sensing volume 14 issue 12 on pages 2764. 10.3390/rs14122764