LiDAR-IMU odometry based on VB-SIEKF

Most of the existing LiDAR-IMU odometry algorithms ignore the variations of process noise and measurement noise, and the traditional filtering methods use linearized rotation matrices for updating, which bring estimation errors in large-angle rotations. To solve the above problems, the paper proposes a novel laser inertial mileage calculation method by combining the variational Bayesian method with Lie group and Lie algebra representation, which significantly improves the accuracy, robustness and computational efficiency of the system, and has high innovation and application value.