| Autor: |
Ghanizadegan, Khashayar, Hashim, Hashim A. |
| Zdroj: |
IEEE Transactions on Instrumentation and Measurement; 2025, Vol. 74 Issue: 1 p1-13, 13p |
| Abstrakt: |
This article investigates the orientation, position, and linear velocity estimation problem of a rigid-body moving in 3-D space with six degrees-of-freedom (6-DoF). The highly nonlinear navigation kinematics are formulated to ensure global representation of the navigation problem. A computationally efficient quaternion-based navigation unscented Kalman filter (QNUKF) is proposed to imitate the true nonlinear navigation kinematics and utilize onboard visual-inertial navigation (VIN) units to achieve successful Global Positioning System (GPS)-denied navigation. The proposed QNUKF is designed in the discrete form to operate based on the data fusion of photographs garnered by a vision unit (stereo or monocular camera) and information collected by a low-cost inertial measurement unit (IMU). The photographs are processed to extract feature points in 3-D space, while the six-axis IMU supplies angular velocity and accelerometer measurements expressed with respect to the body frame. Robustness and effectiveness of the proposed QNUKF have been confirmed through experiments on a real-world dataset collected by a drone navigating in 3-D and consisting of stereo images and six-axis IMU measurements. Also, the proposed approach is validated against state-of-the-art filtering techniques. |
| Databáze: |
Supplemental Index |
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