# IMU-based Online Multi-lidar Calibration

## TL;DR

This paper introduces a reliable, markerless, IMU-based method for online multi-lidar extrinsic calibration on vehicles, improving accuracy without odometry or fiducial markers, validated on real test vehicle data.

## Contribution

The paper presents a novel IMU-based approach for online multi-lidar calibration that does not require odometry or fiducial markers, using feature matching and observability criteria.

## Key findings

- Successful validation on Scania test vehicles
- Improved calibration accuracy without odometry
- Efficient subset selection using mutual information

## Abstract

Modern autonomous systems typically use several sensors for perception. For best performance, accurate and reliable extrinsic calibration is necessary. In this research, we propose a reliable technique for the extrinsic calibration of several lidars on a vehicle without the need for odometry estimation or fiducial markers. First, our method generates an initial guess of the extrinsics by matching the raw signals of IMUs co-located with each lidar. This initial guess is then used in ICP and point cloud feature matching which refines and verifies this estimate. Furthermore, we can use observability criteria to choose a subset of the IMU measurements that have the highest mutual information -- rather than comparing all the readings. We have successfully validated our methodology using data gathered from Scania test vehicles.