TY - GEN

T1 - Timestamp Offset Calibration for an IMU-Camera System Under Interval Uncertainty

AU - Voges, Raphael

AU - Wagner, Bernardo

N1 - DBLP's bibliographic metadata records provided through http://dblp.org/search/publ/api are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions. Publisher Copyright: © 2018 IEEE. Copyright: Copyright 2019 Elsevier B.V., All rights reserved.

PY - 2018/12/27

Y1 - 2018/12/27

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85062943411&partnerID=8YFLogxK

U2 - 10.1109/iros.2018.8594237

DO - 10.1109/iros.2018.8594237

M3 - Conference contribution

T3 - IEEE International Conference on Intelligent Robots and Systems

SP - 377

EP - 384

BT - 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2018

CY - Madrid, Spain

T2 - 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Y2 - 1 October 2018

ER -