Observability-aware online multi-lidar extrinsic calibration

TL;DR

This paper introduces a real-time, observability-aware method for multi-lidar extrinsic calibration that does not require fiducial markers, using GNSS data and mutual information to improve robustness and accuracy.

Contribution

The paper presents a novel real-time calibration system that selects optimal pose subsets based on observability criteria, enhancing robustness without fiducial markers.

Findings

Accurately calibrates multiple lidars in real-time.

Effective on various sensor configurations.

Validated with extensive vehicle data.

Abstract

Accurate and robust extrinsic calibration is necessary for deploying autonomous systems which need multiple sensors for perception. In this paper, we present a robust system for real-time extrinsic calibration of multiple lidars in vehicle base frame without the need for any fiducial markers or features. We base our approach on matching absolute GNSS and estimated lidar poses in real-time. Comparing rotation components allows us to improve the robustness of the solution than traditional least-square approach comparing translation components only. Additionally, instead of comparing all corresponding poses, we select poses comprising maximum mutual information based on our novel observability criteria. This allows us to identify a subset of the poses helpful for real-time calibration. We also provide stopping criteria for ensuring calibration completion. To validate our approach extensive tests were carried out on data collected using Scania test vehicles (7 sequences for a total of ~ 6.5 Km). The results presented in this paper show that our approach is able to accurately determine the extrinsic calibration for various combinations of sensor setups.