Journal
IEEE ROBOTICS AND AUTOMATION LETTERS
Volume 7, Issue 2, Pages 952-959Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LRA.2021.3136241
Keywords
Localization; sensor fusion; visual-inertial SLAM; indoor magnetic field; MSCKF
Categories
Funding
- CEA-List
Ask authors/readers for more resources
This letter proposes a tightly-coupled fusion of visual, inertial and magnetic data for long-term indoor localization. It extends the Multi-State Constraint Kalman Filter (MSCKF) by incorporating a magnetic map, resulting in improved accuracy over extended periods of time.
We propose in this letter a tightly-coupled fusion of visual, inertial and magnetic data for long-term localization in indoor environment. Unlike state-of-the-art Visual-Inertial SLAM (VISLAM) solutions that reuse visual map to prevent drift, we present in this letter an extension of the Multi-State Constraint Kalman Filter (MSCKF) that takes advantage of a magnetic map. It makes our solution more robust to variations of the environment appearance. The experimental results demonstrate that the localization accuracy of the proposed approach is almost the same over time periods longer than a year.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available