This master thesis project was done together with Saab Dynamics in Linköping the spring of 2022 and aims to perform an online IMU-camera calibration using an AprilTag board. Experiments are conducted on two different types of datasets, the public dataset Euroc and internal datasets from Saab. The calibration is done iteratively by solving a series of nonlinear optimization problems without any initial knowledge of the sensor configuration. The method is largely based on work by Huang and collaborators. Other than just finding the transformation between the IMU and the camera, the biases in the IMU, and the time delay between the two sensors are also explored. By comparing the resulting transformation with Kalibr, the current state of the art offline calibration toolbox, it is possible to conclude that the model can find and correct for the biases in the gyroscope. Therefore it is important to include these biases in the model. The model is able to roughly find the time shift between the two sensors but has more difficulties correcting for it. The thesis also aims to explore ways of compiling a good dataset for calibration. Results show that it is desirable to avoid rapid movements as well as images gathered at distances from the AprilTag board that very a lot. Also, having a shorter exposure time is useful to not lose AprilTag detections.