Research Article
LiDAR Map Construction Using Improved R-T-S Smoothing Assisted Extended Kalman Filter
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@INPROCEEDINGS{10.1007/978-3-030-82562-1_50, author={Bo Zhang and Meng Wang and Shuhui Bi and Fukun Li}, title={LiDAR Map Construction Using Improved R-T-S Smoothing Assisted Extended Kalman Filter}, proceedings={Multimedia Technology and Enhanced Learning. Third EAI International Conference, ICMTEL 2021, Virtual Event, April 8--9, 2021, Proceedings, Part I}, proceedings_a={ICMTEL}, year={2021}, month={7}, keywords={LiDAR Extended Kalman filter R-T-S smoothing}, doi={10.1007/978-3-030-82562-1_50} }- Bo Zhang
Meng Wang
Shuhui Bi
Fukun Li
Year: 2021
LiDAR Map Construction Using Improved R-T-S Smoothing Assisted Extended Kalman Filter
ICMTEL
Springer
DOI: 10.1007/978-3-030-82562-1_50
Abstract
On account of the low accuracy of boundary point cloud information during map construction of LiDAR used in mobile robots, an data processing scheme based on extended Kalman filter (EKF) and improved R-T-S smoothing and averaging is proposed to obtain accurate point cloud information. The proposed scheme can remove some noise points and make the map boundary more smoother and more accurate. The experimental results show that comparying with the original data, the proposed data processing scheme could reduce the position error of point cloud information effectively.
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