Piecewise Linear De-skewing for LiDAR Inertial Odometry
This work addresses motion distortion issues for LiDAR-based navigation systems in robotics or autonomous vehicles, but it is incremental as it builds on existing LIO algorithms.
The paper tackled motion distortion in LiDAR inertial odometry caused by fast movement by proposing a piecewise linear de-skewing algorithm using IMU data, resulting in improved performance for existing LIO algorithms in fast-movement scenarios.
Light detection and ranging (LiDAR) on a moving agent could suffer from motion distortion due to simultaneous rotation of the LiDAR and fast movement of the agent. An accurate piecewise linear de skewing algorithm is proposed to correct the motion distortions for LiDAR inertial odometry (LIO) using high frequency motion information provided by an Inertial Measurement Unit (IMU). Experimental results show that the proposed algorithm can be adopted to improve the performance of existing LIO algorithms especially in cases of fast movement.