A pose estimation method based on stereo vision and inertial navigation fusion
A pose estimation method based on stereo vision and inertial navigation fusion
- Author(s): H. Che 1 ; G. Wang 2 ; C. Shi 1
- DOI: 10.1049/icp.2021.0411
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- Author(s): H. Che 1 ; G. Wang 2 ; C. Shi 1
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View affiliations
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Affiliations:
1:
Beijing Key Laboratory of Metro Fire and Passenger Transportation Safety , China Academy of Safety Science and Technology , Beijing 100012, China ;
2: School of Automation , Beijing University of Posts and Telecommunications , Beijing 100876, China
Source:
CSAA/IET International Conference on Aircraft Utility Systems (AUS 2020),
2021
p.
1173 – 1178
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Affiliations:
1:
Beijing Key Laboratory of Metro Fire and Passenger Transportation Safety , China Academy of Safety Science and Technology , Beijing 100012, China ;
- Conference: CSAA/IET International Conference on Aircraft Utility Systems (AUS 2020)
- DOI: 10.1049/icp.2021.0411
- ISBN: 978-1-83953-419-5
- Location: Online Conference
- Conference date: 18-21 September 2020
- Format: PDF
Aiming at the problem of autonomous positioning of unmanned aerial vehicles in unstructured and complex environment, a simultaneous localization and mapping (SLAM) construction algorithm based on the fusion of stereo camera and inertial navigation device is proposed. The algorithm is divided into two parts: front end and back end. Adopt a local pose estimation method based on sparse feature points, and propose a feature management method and an image frame tracking method based on the inertial measurement unit (IMU) uncertainty model for feature matching and tracking, respectively, which can effectively improve the efficiency and accuracy of feature matching. A graph optimization method that combines stereo information and inertial device information. The unmanned aerial vehicle (UAV) data set Euroc test results show that the SLAM algorithm has good comprehensive performance and can meet the autonomous positioning needs of unmanned aerial vehicles in unstructured and complex environments.
Inspec keywords: stereo image processing; cameras; robot vision; optimisation; SLAM (robots); image matching; inertial navigation; position control; pose estimation; feature extraction; graph theory; autonomous aerial vehicles; image fusion
Subjects: Telerobotics; Computer vision and image processing techniques; Spatial variables control; Optimisation techniques; Image recognition; Optimisation techniques; Combinatorial mathematics; Combinatorial mathematics; Aerospace control; Mobile robots