Not logged in.
Quick Search - Contribution
Contribution Details
| Type | Journal Article |
| Scope | Discipline-based scholarship |
| Title | Simultaneous state initialization and gyroscope bias calibration in visual inertial aided navigation |
| Organization Unit | |
| Authors |
|
| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Language |
|
| Journal Title | IEEE Robotics and Automation Letters |
| Publisher | Institute of Electrical and Electronics Engineers |
| Geographical Reach | international |
| ISSN | 2377-3766 |
| Volume | 2 |
| Number | 1 |
| Page Range | 18 - 25 |
| Date | 2017 |
| Abstract Text | State of the art approaches for visual-inertial sensor fusion use filter-based or optimization-based algorithms. Due to the nonlinearity of the system, a poor initialization can have a dramatic impact on the performance of these estimation methods. Recently, a closed-form solution providing such an initialization was derived in [1]. That solution determines the velocity (angular and linear) of a monocular camera in metric units by only using inertial measurements and image features acquired in a short time interval. In this letter, we study the impact of noisy sensors on the performance of this closed-form solution. We show that the gyroscope bias, not accounted for in [1], significantly affects the performance of the method. Therefore, we introduce a new method to automatically estimate this bias. Compared to the original method, the new approach now models the gyroscope bias and is robust to it. The performance of the proposed approach is successfully demonstrated on real data from a quadrotor MAV. |
| Related URLs | |
| Digital Object Identifier | 10.1109/LRA.2016.2521413 |
| Other Identification Number | merlin-id:13323 |
| PDF File |
Download from ZORA
|
| Export |
BibTeX
EP3 XML (ZORA)
|
| Keywords | calibration, filtering theory, gyroscopes, inertial navigation, mobile robots, optimisation, sensor fusion, space vehicles, autonomous mobile robots, closed-form solution, filter-based algorithms, gyroscope bias calibration, image features, inertial measurements, metric units, micro aerial vehicles, monocular camera, noisy sensors, optimization-based algorithms, quadrotor MAV, sensor fusion, simultaneous state initialization, visual inertial aided navigation, Calibration, Cameras, Closed-form solutions, Gyroscopes, Linear systems, Robot sensing systems, Visualization, Localization, Sensor Fusion, Sensor fusion, Visual-Based Navigation, localization, visual-based navigation |
| Additional Information | © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |