Visual-Inertial Odometry with Robust Initialization and Online Scale Estimation
- Title
- Visual-Inertial Odometry with Robust Initialization and Online Scale Estimation
- Author
- 임종우
- Keywords
- visual-inertial odometry; UAV navigation; sensor fusion; optimization
- Issue Date
- 2018-12
- Publisher
- MDPI
- Citation
- SENSORS, v. 18, no. 12, Article no. 4287
- Abstract
- Visual-inertial odometry (VIO) has recently received much attention for efficient and accurate ego-motion estimation of unmanned aerial vehicle systems (UAVs). Recent studies have shown that optimization-based algorithms achieve typically high accuracy when given enough amount of information, but occasionally suffer from divergence when solving highly non-linear problems. Further, their performance significantly depends on the accuracy of the initialization of inertial measurement unit (IMU) parameters. In this paper, we propose a novel VIO algorithm of estimating the motional state of UAVs with high accuracy. The main technical contributions are the fusion of visual information and pre-integrated inertial measurements in a joint optimization framework and the stable initialization of scale and gravity using relative pose constraints. To account for the ambiguity and uncertainty of VIO initialization, a local scale parameter is adopted in the online optimization. Quantitative comparisons with the state-of-the-art algorithms on the European Robotics Challenge (EuRoC) dataset verify the efficacy and accuracy of the proposed method.
- URI
- https://www.mdpi.com/1424-8220/18/12/4287https://repository.hanyang.ac.kr/handle/20.500.11754/121053
- ISSN
- 1424-8220
- DOI
- 10.3390/s18124287
- Appears in Collections:
- COLLEGE OF ENGINEERING[S](공과대학) > COMPUTER SCIENCE(컴퓨터소프트웨어학부) > Articles
- Files in This Item:
- Visual-Inertial Odometry with Robust Initialization and Online Scale Estimation.pdfDownload
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