Online Extrinsic Calibration Based on Per-Sensor Ego-Motion Using Dual Quaternions

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 fast local along with method to verify the globality of approach. Additionally, means integrating previous knowledge, example, common ground plane planar motion, are described. algorithms evaluated simulated data publicly available dataset containing RGB-D camera images. Further, our tested KITTI odometry dataset, which provides lidar stereo systems mounted vehicle. evaluation confirms short run time, state-of-the-art accuracy, as well capability while retaining global optimality solution at any time.