Forkel, Bianca (Universität der Bundeswehr München), Berthold, Philipp (Bundeswehr University Munich), Maehlisch, Mirko (University of German Military Forces Munich)

An Extrinsic Sensor Calibration Framework for Precise Probabilistic Joint Calibration of Camera, LiDAR, and Radar

Scheduled for presentation during the Regular Session "S43b-Multi-Sensor Fusion and Perception for Robust Autonomous Driving" (FR-EA-T43), Friday, November 21, 2025, 14:50−14:50, Stradbroke

2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC), November 18-21, 2025, Gold Coast, Australia

This information is tentative and subject to change. Compiled on October 18, 2025

Abstract

Accurate sensor data fusion requires accurate knowledge of the sensors' relative mounting poses. To calibrate the sensor setup of autonomous vehicles, we propose a tool for the joint 6D extrinsic calibration of cameras, LiDAR sensors, and radar sensors. Our optimization-based method achieves high accuracy by probabilistically accounting for measurement uncertainties and employing an advanced calibration target. In addition to optimized visual markers and geometric features detectable by cameras and LiDAR sensors, the calibration target includes a radar Doppler simulator. This enables radar sensors to detect the calibration target with high accuracy and unambiguity. The proposed calibration tool is quantitatively evaluated on real-world data and released as an open-source ROS package.