Continuous-Time Spline Visual-Inertial Odometry

Jiawei Mo, Junaed Sattar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations


We propose a continuous-time spline-based formulation for visual-inertial odometry (VIO). Specifically, we model the poses as a cubic spline, whose temporal derivatives are used to synthesize linear acceleration and angular velocity, which are compared to the measurements from the inertial measurement unit (IMU) for optimal state estimation. The spline boundary conditions create constraints between the camera and the IMU, with which we formulate VIO as a constrained nonlinear optimization problem. Continuous-time pose representation makes it possible to address many VIO challenges, e.g., rolling shutter distortion and sensors that may lack synchronization. We conduct experiments on two publicly available datasets that demonstrate the state-of-the-art accuracy and real-time computational efficiency of our method.

Original languageEnglish (US)
Title of host publication2022 IEEE International Conference on Robotics and Automation, ICRA 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages7
ISBN (Electronic)9781728196817
StatePublished - 2022
Event39th IEEE International Conference on Robotics and Automation, ICRA 2022 - Philadelphia, United States
Duration: May 23 2022May 27 2022

Publication series

Name2022 International Conference on Robotics and Automation (ICRA)


Conference39th IEEE International Conference on Robotics and Automation, ICRA 2022
Country/TerritoryUnited States

Bibliographical note

Funding Information:
This work was partially supported by the Minnesota Robotics Institute Seed (MnRI) Grant and the National Science Foundation award IIS-#1637875.

Publisher Copyright:
© 2022 IEEE.


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