VMC-LIO: Incorporating Vehicle Motion Characteristics in LiDAR Inertial Odometry

被引:0
作者
Sun, Chao [1 ,2 ]
Leng, Jianghao [2 ]
Wang, Bo [1 ]
Liang, Weiqiang [3 ]
Jia, Bowen [4 ]
Huang, Zhishuai [2 ]
Lu, Bing [1 ]
Li, Jiajun [2 ]
机构
[1] Beijing Inst Technol, Shenzhen Automot Res Inst, Shenzhen 518118, Peoples R China
[2] Beijing Inst Technol, Sch Mech Engn, Natl Engn Lab Elect Vehicles, Beijing 100081, Peoples R China
[3] Guangzhou Automobile Grp Co Ltd, GAC Automot Res & Dev Ctr, Guangzhou 510623, Peoples R China
[4] China Elect Standardizat Inst, Internet Vehicles & Nav Off Digital Ctr, Beijing 100007, Peoples R China
基金
国家重点研发计划;
关键词
Laser radar; Odometry; Kinematics; Three-dimensional displays; Odometers; Cameras; Manifolds; State estimation; vehicle LiDAR inertial odometry; ground surface; 3D vehicle kinematic model; ROBUST; FUSION; VINS;
D O I
10.1109/TVT.2024.3384955
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper proposes a novel LiDAR inertial odometry (LIO) incorporating vehicle motion characteristics (VMC) tailored for ground vehicles. While most advanced LIO systems are designed for 6 degrees of freedom (DOF) SE(3), which are not ideally suited for ground vehicles, this paper investigates the performance of the vehicle-LiDAR-IMU system by considering the vehicle motion characteristics. The system combines IMU propagation, LiDAR measurements, ground surface measurements and 3 dimension (3D) vehicle kinematic model measurements within an iterated Kalman filter framework. To ensure a robust system bootstrapping, the temporal and spatial parameters of the vehicle-LiDAR-IMU system are calibrated first. Then, in addition to the IMU preintegration and LiDAR measurements, constraints are established between the ground surface and the vehicle pose by calculating the normal of the ground beneath the vehicle in the local point cloud map. Moreover, measurements of the 3D vehicle kinematic model with angular velocity and velocity constraints are adopted. Ground surface is considered in the 3D kinematic model for vehicle angular velocity calculation. The results from simulations and vehicle experiments demonstrate that the proposed method improves accuracy compared with state-of-the-art LiDAR SLAM methods while maintaining a real-time implementation capability for vehicles.
引用
收藏
页码:12315 / 12327
页数:13
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