Cooperative Visual-LiDAR Extrinsic Calibration Technology for Intersection Vehicle-Infrastructure: A review

TL;DR

This review paper discusses the importance and challenges of multi-end camera-LiDAR extrinsic calibration in intersection vehicle-infrastructure systems, emphasizing recent advances and future directions for cooperative perception.

Contribution

It provides a comprehensive analysis of calibration methods for multi-end camera-LiDAR systems from various perspectives, highlighting their applications and significance in autonomous driving at intersections.

Findings

Multi-end calibration is crucial for accurate environmental perception.

Infrastructure-assisted calibration enhances vehicle perception capabilities.

Technical complexities in multi-end calibration require ongoing research.

Abstract

In the typical urban intersection scenario, both vehicles and infrastructures are equipped with visual and LiDAR sensors. By successfully integrating the data from vehicle-side and road monitoring devices, a more comprehensive and accurate environmental perception and information acquisition can be achieved. The Calibration of sensors, as an essential component of autonomous driving technology, has consistently drawn significant attention. Particularly in scenarios involving multiple sensors collaboratively perceiving and addressing localization challenges, the requirement for inter-sensor calibration becomes crucial. Recent years have witnessed the emergence of the concept of multi-end cooperation, where infrastructure captures and transmits surrounding environment information to vehicles, bolstering their perception capabilities while mitigating costs. However, this also poses technical complexities, underscoring the pressing need for diverse end calibration. Camera and LiDAR, the bedrock sensors in autonomous driving, exhibit expansive applicability. This paper comprehensively examines and analyzes the calibration of multi-end camera-LiDAR setups from vehicle, roadside, and vehicle-road cooperation perspectives, outlining their relevant applications and profound significance. Concluding with a summary, we present our future-oriented ideas and hypotheses.