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Conference Paper (international conference)

Sensor Fusion for simple walking robot using low-level implementation of Extended Kalman Filter

Anderle Milan, Čelikovský Sergej

: IFAC-PapersOnLine. Volume 51, Issue 13. : 2nd IFAC Conference on Modelling, Identification and Control of Nonlinear Systems MICNON 2018, p. 43-48

: Second IFAC Conference on Modelling, Identification and Control of Nonlinear Systems, (Guadalajara, MX, 20180620)

: GA17-04682S, GA ČR

: Filtering and smoothing, Digital implementation, Walking robot

: 10.1016/j.ifacol.2018.07.252

(eng): The main aim of this paper depicts in design and implementation of the Extended\nKalman Filter for a nonlinear system in an application of a sensor fusion from a practical point of view. The sensor fusion is a typical data processing problem in mechanical systems where individual measurements of (angular) positions, velocities or accelerations are done independently on each other but the measured values are correlated to each other via dynamics of the system. Moreover, the measurement is corrupted by noise. The sensor fusion technique is capable to gain proper information about positions, velocities or accelerations from inaccurate\nmeasurement. In background of the sensor fusion algorithm, in our particular case, works the Extended Kalman Filter. Its adaptation for a simple mechanical system represented by a nonlinear system are object of the research in this paper related to usage of the Extended Kalman Filter on a low cost hardware.

: BC

: 20205

07.01.2019 - 08:39