A Joint Extrinsic Calibration Tool for Radar, Camera and Lidar

Abstract

We address joint extrinsic calibration of lidar, camera and radar sensors. To simplify calibration, we propose a single calibration target design for all three modalities, and implement our approach in an open-source tool with bindings to Robot Operating System (ROS). Our tool features three optimization configurations, namely using error terms for a minimal number of sensor pairs, or using terms for all sensor pairs in combination with loop closure constraints, or by adding terms for structure estimation in a probabilistic model. Apart from relative calibration where relative transformations between sensors are computed, our work also addresses absolute calibration that includes calibration with respect to the mobile robot's body. Two methods are compared to estimate the body reference frame using an external laser scanner, one based on markers and the other based on manual annotation of the laser scan. In the experiments, we evaluate the three configurations for relative calibration. Our results show that using terms for all sensor pairs is most robust, especially for lidar to radar, when minimum five board locations are used. For absolute calibration the median rotation error around the vertical axis reduces from 1 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">°</sup> before calibration, to 0.33 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">°</sup> using the markers and 0.02 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">°</sup> with manual annotations.