Research Article
Lidar/IMU Integrated Navigation and Positioning Method
@INPROCEEDINGS{10.1007/978-3-030-82562-1_38, author={Zhigang Wang and Jiehua Liao and Hang Guo and Min Yu}, title={Lidar/IMU Integrated Navigation and Positioning Method}, 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={R-fans 16-line lidar Closed loop Non-closed loop LOAM algorithm APF algorithm}, doi={10.1007/978-3-030-82562-1_38} }- Zhigang Wang
Jiehua Liao
Hang Guo
Min Yu
Year: 2021
Lidar/IMU Integrated Navigation and Positioning Method
ICMTEL
Springer
DOI: 10.1007/978-3-030-82562-1_38
Abstract
Aiming at the problem of large positioning accuracy of LiDAR odometry and mapping (LOAM) algorithm, this paper proposes a LOAM algorithm fusion Adaptive Particle Filter (APF) algorithm. Experiments show that the trajectory of the APF algorithm using the LOAM algorithm was half the accuracy of the trajectory using the LOAM algorithm. In order to better verify the accuracy effect, the R-fans 16-line laser radar was used to compare and analyze the test under closed and non-closed routes. The results show that under the closed route, the LOAM algorithm combines the APF algorithm to provide the accurate position trajectory for the car. In the non-closed route, due to the lack of closed-loop constraints, the motion distortion of the car is caused by the accumulation of errors. Through experiments, using the LOAM algorithm to merge the APF algorithm in the non-closed loop could also effectively compensate the motion distortion and filter out the noise, so as to achieve the effect of the trajectory correction, reduce the error with the real trajectory, and improve the positioning accuracy.
