LiDAR-Inertial Simultaneous Localization and Mapping with Continuous Motion Correction and Intensity Assistance for Degraded Environments

Yang Zeng; Feng Xu; Jihua Ming; Junjie Shen; Ran Liu

doi:10.3788/LOP250433

Laser & Optoelectronics Progress, Volume. 62, Issue 16, 1628002(2025)

LiDAR-Inertial Simultaneous Localization and Mapping with Continuous Motion Correction and Intensity Assistance for Degraded Environments

Yang Zeng^1,2, Feng Xu^1,2、*, Jihua Ming^1,2, Junjie Shen^1,2, and Ran Liu^1,2

Author Affiliations

¹School of Information and Control Engineering, Southwest University of Science and Technology, Mianyang 621010, Sichuan , China

²Sichuan Key Laboratory of Robot Technology Used for Special Environment, Mianyang 621010, Sichuan , China

show less

Abstract Get PDF(in Chinese)

Figures & Tables(10)

Fig. 1. System framework diagram

Download full size

Fig. 2. Schematic diagram of Slerp interpolation

Download full size

Fig. 3. Trajectory comparison diagrams of different sequences in the KITTI dataset. (a) Global trajectory of the KITTI 01 sequence; (b) global trajectory of the KITTI 10 sequence; (c) local trajectory of the KITTI 01 sequence; (d) local trajectory of the KITTI 10 sequence

Download full size

Fig. 4. Comparison of ATE of different sequences in KITTI dataset. (a) 01 sequence; (b) 04 sequence; (c) 07 sequence; (d) 10 sequence

Download full size

Fig. 5. Mapping results of various algorithms on the SubT-MRS dataset. (a) UGV 1 scene; (b) UGV 3 scene; (c) Laurel Caverns scene

Download full size

Fig. 6. Trajectory comparison of different algorithms on the SubT-MRS dataset. (a) UGV 1 scene; (b) UGV 3 scene; (c) Laurel Caverns scene

Download full size

Table 1. Sensor parameters of the KITTI dataset

View table

Table 1. Sensor parameters of the KITTI dataset

Sensor	Resolution	Field of view	Frequency /Hz	Axis /line number
2 color/grayscale cameras	1392 pixel×512 pixel	90.0°×35.0°	10	—
Velodyne HDL-64E	0.09° angular resolution	360.0°×26.8°	10	64 lines
GPS/IMU navigation system	0.02 m，0.1°	—	100	6-axis

Table 2. Sensor parameters of the SubT-MRS dataset

View table

Table 2. Sensor parameters of the SubT-MRS dataset

Sensor	Resolution	Field of view	Frequency /Hz	Axis /line number
Velodyne VLP-16	0.1°angular resolution	360°×30°	10	16 lines
Epson M-G365 IMU	0.08 （°）/√hr	—	10	6-axis
LI-Xavier-Kit RGB camera	686 pixel×816 pixel	—	24	—
FLIR Boson thermal camera	512 pixel×640 pixel	—	60	—

Table 3. Comparison of ATE on the KITTI dataset

View table

Table 3. Comparison of ATE on the KITTI dataset

SLAM algorithm	Sequence
SLAM algorithm	01	04	07	10
A-LOAM	36.8362	1.1165	2.0096	12.6714
LeGO-LOAM	210.7686	0.4764	1.3584	1.6821
LIO-SAM	21.3409	0.2852	0.7984	2.4738
Proposed^{^}	20.4423	0.2852	0.7950	2.3143
Proposed^{^^}	20.7103	0.2840	0.7465	2.3083
Proposed	20.2680	0.2839	0.7869	2.2622

Table 4. Comparison of ATE on the SubT-MRS dataset
View table
Table 4. Comparison of ATE on the SubT-MRS dataset
SLAM algorithm Scene
UGV 1 UGV 3 Laurel Caverns
FAST-LIO2 0.4717 — —
LIO-SAM 0.5575 1.3234 19.7650
Proposed 0.4414 1.4333 19.0204

Tools

Get Citation

Copy Citation Text

Yang Zeng, Feng Xu, Jihua Ming, Junjie Shen, Ran Liu. LiDAR-Inertial Simultaneous Localization and Mapping with Continuous Motion Correction and Intensity Assistance for Degraded Environments[J]. Laser & Optoelectronics Progress, 2025, 62(16): 1628002

Download Citation

EndNote(RIS)BibTex Plain Text

Set citation alerts for article

Save article for my favorites