Multi-LiCa: A Motion and Targetless Multi LiDAR-to-LiDAR Calibration Framework

TL;DR

Multi-LiCa introduces an automatic, targetless calibration framework for multiple LiDAR sensors on autonomous vehicles, using a two-step feature-based and GICP-based registration process, applicable to various sensor configurations.

Contribution

It presents a novel, fully automatic multi-LiDAR calibration method that does not require targets or initial transformations, enhancing flexibility and accuracy.

Findings

Outperforms existing calibration methods in accuracy.

Applicable to any number of sensors with overlapping fields of view.

Generalizes well across different sensor setups and scenarios.

Abstract

Today's autonomous vehicles rely on a multitude of sensors to perceive their environment. To improve the perception or create redundancy, the sensor's alignment relative to each other must be known. With Multi-LiCa, we present a novel approach for the alignment, e.g. calibration. We present an automatic motion- and targetless approach for the extrinsic multi LiDAR-to-LiDAR calibration without the need for additional sensor modalities or an initial transformation input. We propose a two-step process with feature-based matching for the coarse alignment and a GICP-based fine registration in combination with a cost-based matching strategy. Our approach can be applied to any number of sensors and positions if there is a partial overlap between the field of view of single sensors. We show that our pipeline is better generalized to different sensor setups and scenarios and is on par or better in calibration accuracy than existing approaches. The presented framework is integrated in ROS 2 but can also be used as a standalone application. To build upon our work, our source code is available at: https://github.com/TUMFTM/Multi_LiCa.