Abstract
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.
Original language | English |
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Pages (from-to) | 1-13 |
Number of pages | 13 |
Journal | IEEE Transactions on Vehicular Technology |
DOIs | |
Publication status | Accepted/In press - 2024 |
Keywords
- 3D vehicle kinematic model
- Cameras
- Kinematics
- Laser radar
- Manifolds
- Odometers
- Odometry
- Three-dimensional displays
- ground surface
- state estimation
- vehicle LiDAR inertial odometry