Timestamp Offset Calibration for an IMU-Camera System Under Interval Uncertainty


To properly fuse IMU and camera information for robotics applications, the relative timestamp offset between both sensors' data streams has to be considered. However, finding the exact timestamp offset is often impossible. Thus, it is necessary to additionally consider the offset’s uncertainty if we want to produce reliable results. In order to find the offset and its uncertainty, we determine orientation estimates from IMU and camera under interval uncertainty. Subsequently, these intervals are used as a common representation for our bounded-error approach that finds an interval enclosing the true offset while also modeling the uncertainty. Calibration data can be acquired in a few seconds using a simple setup of IMU, camera and camera target. Results using both simulated and real data demonstrate that we are able to determine the offset to an accuracy of 20 ms with a computation time that is suitable for future online applications. Here, our approach could be used to monitor the timestamp offset in a guaranteed way. Additionally, our method can be adapted to determine an interval for the rotation between both sensors. While this increases the computation time drastically, it also enhances the accuracy of the timestamp offset to less than 10 ms.

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Raphael Voges
Raphael Voges
Doctor in Robotics

My research interests include error modeling, sensor fusion, SLAM, state estimation and AI in the context of autonomous driving.