  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.
