Sensor Aware Lidar Odometry
Dmitri Kovalenko, Mikhail Korobkin, and Andrey Minin
Yandex LLC, Russia
The 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 a novel outlier correspondence rejection scheme. The method is scored high on KITTI leaderboard with 1.5% positioning error. That of 3.7% is achieved in comparison with the LOAM method on the internal dataset.