Convergence of the EKF in mark-based vision for 3D vehicle tracking
| Authors: | Delgado Emma, University of Vigo, Spain
Barreiro A., University of Vigo, Spain
Baltar J.A., University of Vigo, Spain |
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| Topic: | 7.5 Intelligent Autonomous Vehicles |
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| Session: | Intelligent Autonomous Vehicles |
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| Keywords: | Dynamic vision, Nonlinear observers, Extended Kalman Filters, Domain of attraction, Convergence, Vehicle tracking, Pose estimation. |
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Abstract
In this paper, the extended Kalman filtering (EKF) technique is considered for 3-dimensional tracking of vehicle movement using a fixed camera that provides vehicle images showing several marks, easily detectable, fixed to the vehicle body. The algorithm will be implemented in a minihelicopter hover-stabilization application. For this problem, we present results on the convergence and the domain of attraction of the non-linear observation scheme as a function of the tuning filter parameters: the initial value of the covariance and the robustifying parameter alpha.
