Sensor Aware Lidar Odometry
This work addresses incremental improvements in localization accuracy for autonomous vehicles or robotics.
The paper tackles the problem of improving lidar odometry precision by integrating sensor physics knowledge into the computation, resulting in a positioning error of 1.37% on the KITTI leaderboard and 3.67% compared to LOAM on an internal dataset.
A lidar odometry method, integrating into the computation the knowledge about the physics of the sensor, is proposed. A model of measurement error enables higher precision in estimation of the point normal covariance. Adjacent laser beams are used in an outlier correspondence rejection scheme. The method is ranked in the KITTI's leaderboard with 1.37% positioning error. 3.67% is achieved in comparison with the LOAM method on the internal dataset.