In this work, we propose an approach for extrinsic sensor calibration from per-sensor ego-motion estimates. Our problem formulation is based on dual quaternions, enabling two different online capable solving approaches. We provide a certifiable globally optimal and a fast local approach along with a method to verify the globality of the local approach. Additionally, means for integrating previous knowledge, for example, a common ground plane for planar sensor motion, are described. Our algorithms are evaluated on simulated data and on a publicly available dataset containing RGB-D camera images. Further, our online calibration approach is tested on the KITTI odometry dataset, which provides data of a lidar and two stereo camera systems mounted on a vehicle. Our evaluation confirms the short run time, state-of-the-art accuracy, as well as online capability of our approach while retaining the global optimality of the solution at any time.
@article{arxiv.2101.11440,
title = {Online Extrinsic Calibration based on Per-Sensor Ego-Motion Using Dual Quaternions},
author = {Markus Horn and Thomas Wodtko and Michael Buchholz and Klaus Dietmayer},
journal= {arXiv preprint arXiv:2101.11440},
year = {2021}
}