Abstract
This paper develops a monocular vision-aided inertial navigation system based on the factored extended Kalman filter (EKF) proposed by Bierman and Thornton. The simultaneous localization and mapping (SLAM) algorithm measurement update and propagation steps are formulated in terms of the factored covariance matrix P = UDUT, and a novel method for efficiently adding and removing features from the covariance factors is presented. The system is compared to the standard EKF formulation in navigation performance and computational requirements. The proposed method is shown to improve numerical stability with minimal impact on computational requirements. Flight test results are presented which demonstrate navigation performance with a controller in the loop.
| Original language | English (US) |
|---|---|
| Title of host publication | AIAA Guidance, Navigation, and Control Conference |
| Publisher | American Institute of Aeronautics and Astronautics Inc, AIAA |
| ISBN (Print) | 9781624103391 |
| State | Published - Jan 1 2015 |
| Event | AIAA Guidance, Navigation, and Control Conference, 2015 - Kissimmee, United States Duration: Jan 5 2015 → Jan 9 2015 |
Publication series
| Name | AIAA Guidance, Navigation, and Control Conference, 2013 |
|---|
Other
| Other | AIAA Guidance, Navigation, and Control Conference, 2015 |
|---|---|
| Country | United States |
| City | Kissimmee |
| Period | 1/5/15 → 1/9/15 |
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All Science Journal Classification (ASJC) codes
- Electrical and Electronic Engineering
- Aerospace Engineering
- Control and Systems Engineering
Cite this
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A monocular vision-aided inertial navigation system with improved numerical stability. / Magree, Daniel; Johnson, Eric N.
AIAA Guidance, Navigation, and Control Conference. American Institute of Aeronautics and Astronautics Inc, AIAA, 2015. (AIAA Guidance, Navigation, and Control Conference, 2013).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - A monocular vision-aided inertial navigation system with improved numerical stability
AU - Magree, Daniel
AU - Johnson, Eric N.
PY - 2015/1/1
Y1 - 2015/1/1
N2 - This paper develops a monocular vision-aided inertial navigation system based on the factored extended Kalman filter (EKF) proposed by Bierman and Thornton. The simultaneous localization and mapping (SLAM) algorithm measurement update and propagation steps are formulated in terms of the factored covariance matrix P = UDUT, and a novel method for efficiently adding and removing features from the covariance factors is presented. The system is compared to the standard EKF formulation in navigation performance and computational requirements. The proposed method is shown to improve numerical stability with minimal impact on computational requirements. Flight test results are presented which demonstrate navigation performance with a controller in the loop.
AB - This paper develops a monocular vision-aided inertial navigation system based on the factored extended Kalman filter (EKF) proposed by Bierman and Thornton. The simultaneous localization and mapping (SLAM) algorithm measurement update and propagation steps are formulated in terms of the factored covariance matrix P = UDUT, and a novel method for efficiently adding and removing features from the covariance factors is presented. The system is compared to the standard EKF formulation in navigation performance and computational requirements. The proposed method is shown to improve numerical stability with minimal impact on computational requirements. Flight test results are presented which demonstrate navigation performance with a controller in the loop.
UR - http://www.scopus.com/inward/record.url?scp=85019398100&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85019398100&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85019398100
SN - 9781624103391
T3 - AIAA Guidance, Navigation, and Control Conference, 2013
BT - AIAA Guidance, Navigation, and Control Conference
PB - American Institute of Aeronautics and Astronautics Inc, AIAA
ER -