Unscented Particle Filter for Visual-inertial Navigation using IMU and Landmark Measurements
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866908340048625664 |
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| author | Ghanizadegan, Khashayar Hashim, Hashim A. |
| author_facet | Ghanizadegan, Khashayar Hashim, Hashim A. |
| contents | This paper introduces a geometric Quaternion-based Unscented Particle Filter for Visual-Inertial Navigation (QUPF-VIN) specifically designed for a vehicle operating with six degrees of freedom (6 DoF). The proposed QUPF-VIN technique is quaternion-based capturing the inherently nonlinear nature of true navigation kinematics. The filter fuses data from a low-cost inertial measurement unit (IMU) and landmark observations obtained via a vision sensor. The QUPF-VIN is implemented in discrete form to ensure seamless integration with onboard inertial sensing systems. Designed for robustness in GPS-denied environments, the proposed method has been validated through experiments with real-world dataset involving an unmanned aerial vehicle (UAV) equipped with a 6-axis IMU and a stereo camera, operating with 6 DoF. The numerical results demonstrate that the QUPF-VIN provides superior tracking accuracy compared to ground truth data. Additionally, a comparative analysis with a standard Kalman filter-based navigation technique further highlights the enhanced performance of the QUPF-VIN. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_19318 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Unscented Particle Filter for Visual-inertial Navigation using IMU and Landmark Measurements Ghanizadegan, Khashayar Hashim, Hashim A. Robotics Systems and Control This paper introduces a geometric Quaternion-based Unscented Particle Filter for Visual-Inertial Navigation (QUPF-VIN) specifically designed for a vehicle operating with six degrees of freedom (6 DoF). The proposed QUPF-VIN technique is quaternion-based capturing the inherently nonlinear nature of true navigation kinematics. The filter fuses data from a low-cost inertial measurement unit (IMU) and landmark observations obtained via a vision sensor. The QUPF-VIN is implemented in discrete form to ensure seamless integration with onboard inertial sensing systems. Designed for robustness in GPS-denied environments, the proposed method has been validated through experiments with real-world dataset involving an unmanned aerial vehicle (UAV) equipped with a 6-axis IMU and a stereo camera, operating with 6 DoF. The numerical results demonstrate that the QUPF-VIN provides superior tracking accuracy compared to ground truth data. Additionally, a comparative analysis with a standard Kalman filter-based navigation technique further highlights the enhanced performance of the QUPF-VIN. |
| title | Unscented Particle Filter for Visual-inertial Navigation using IMU and Landmark Measurements |
| topic | Robotics Systems and Control |
| url | https://arxiv.org/abs/2504.19318 |