Visual-inertial odometry based on tightly-coupled encoder

Zhangfang Hu; Zhenqian Guo; Yuan Luo; Jian Chen

doi:10.1117/12.2641165

4 January 2023 Visual-inertial odometry based on tightly-coupled encoder

Zhangfang Hu, Zhenqian Guo, Yuan Luo, Jian Chen

Proceedings Volume 12317, Optoelectronic Imaging and Multimedia Technology IX; 123170K (2023) https://doi.org/10.1117/12.2641165
Event: SPIE/COS Photonics Asia, 2022, Online Only

Conference Poster

Abstract

In order to solve the problem of inaccurate scale optimization of visual inertial odometer (VIO) algorithm under uniform motion, this paper presents a Visual-Inertial-Encoder Tightly-Coupled Odometry (VIETO) algorithm, and describes VIETO initialization as an optimal estimation problem in the sense of maximum-a-posteriori (MAP) estimation. Firstly, the pre-integration theory of encoder is introduced in this paper so that the scale and velocity information can be obtained by using the encoder to measure the pre-integration during the visual MAP estimation, which provides a good initial value for the optimal estimation of IMU parameters. Secondly, the encoder error term and random plane constraint are introduced into the visual inertia optimization framework to further constrain pose estimation. Finally, we apply VIETO to the monocular inertial ORB-SLAM3 system. By comparing the algorithm with other similar algorithms on the DS dataset, the results prove the effectiveness of the system.

Conference Presentation

Citation Download Citation

Zhangfang Hu, Zhenqian Guo, Yuan Luo, and Jian Chen "Visual-inertial odometry based on tightly-coupled encoder", Proc. SPIE 12317, Optoelectronic Imaging and Multimedia Technology IX, 123170K (4 January 2023); https://doi.org/10.1117/12.2641165

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available