Interacting Multiple Model Filter Based Autonomous Landing Considering Camera Model Uncertainty

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This paper deals with the state estimation and control for camera-assisted landing. Uncertainties in measurement models, such as lens distortion, can adversely affect the camera's target detection and navigational functions. We propose an effective state estimator based on the Interacting Multiple Model filter to account for the uncertainties in the camera measurement model. We further introduce a phase update rule, which determines the feasibility of autonomous landing in a stochastic manner, and filter and control management logic is proposed by which to handle the different phases. The proposed framework is simulated using a multi-rotor type UAV equipped with a camera and rangefinder in the Gazebo simulation environment. The experiments validate the performance of the framework in terms of accuracy in state estimation and control. © 2021 IEEE.
Publisher
Institute of Electrical and Electronics Engineers Inc.
Issue Date
2021-06
Language
English
Citation

2021 International Conference on Unmanned Aircraft Systems, ICUAS 2021, pp.347 - 353

DOI
10.1109/ICUAS51884.2021.9476701
URI
http://hdl.handle.net/10203/288411
Appears in Collection
AE-Conference Papers(학술회의논문)
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