Adaptive Software Complex for Car Navigation System
Abstract
This article presents the software complex structure of autonomous vehicle navigation system. Navigation algorithms are based on different linearizations of Kalman filter, including perturbation Kalman filter, extended Kalman filter, iterated extended Kalman filter. Navigation system is a multi-mode and can vary accuracy and system CPU load by switching between modes. Different modes correspond to different implementations of the Kalman filter, as well as different motion models. Various implementations of the Kalman filter are used to select estimation accuracy and current CPU load. Different motion models are used to allow system to react instantly to changes in the environment. All switching happens in real time and do not require additional CPU calculations. The system architecture is described using the Unified Modeling Language (UML) and can be implemented in most object-oriented programming languages.
About the Author
A. N. Zabegaev
Keldysh Institute of Applied Mathematics (Russian Academy of Sciences)
Russian Federation
Russian Federation
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Review
For citations:
Zabegaev A.N. Adaptive Software Complex for Car Navigation System. Mekhatronika, Avtomatizatsiya, Upravlenie. 2015;16(2):140-144. (In Russ.)
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