Monocular Vision-inertial Fusion Approach for MAV State Estimation
To improve the pose estimation accuracy of quadrotors MAV(mertial measurement unit), it presented a new algorithm of state estimation for quadrotors. In this paper, a modular Kalman filter framework was designed, which combines the initial pose estimation of the vision part and the IMU-based dynamic...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Control and Information Technology
2018-01-01
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| Series: | Kongzhi Yu Xinxi Jishu |
| Subjects: | |
| Online Access: | http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2096-5427.2018.06.009 |
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| Summary: | To improve the pose estimation accuracy of quadrotors MAV(mertial measurement unit), it presented a new algorithm of state estimation for quadrotors. In this paper, a modular Kalman filter framework was designed, which combines the initial pose estimation of the vision part and the IMU-based dynamic model, and this framework is a new visual inertial odometry. The ARTags were used to obtain pose estimation, and the result was used as the observation of the algorithm. The dynamic model based on IMU was established, and the visual result was added to the state vector for iterations. Since the frequency of IMU is higher than that of the visual result, the most recent state vector is selected when it updates. The algorithm still works well when the visual result is abnormal, and it shows a good performance in the experiment. |
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| ISSN: | 2096-5427 |