# Sensor Aware Lidar Odometry

## TL;DR

This paper introduces a lidar odometry approach that incorporates sensor physics and measurement error modeling, achieving high accuracy and outperforming existing methods on standard benchmarks.

## Contribution

It presents a novel lidar odometry method that models sensor measurement errors and uses beam adjacency for outlier rejection, improving accuracy over prior techniques.

## Key findings

- Ranked 1.37% positioning error on KITTI leaderboard
- Achieves 3.67% improvement over LOAM on internal dataset
- Incorporates sensor physics into odometry estimation

## Abstract

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.