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

0491010 - ÚTIA 2019 RIV NL eng C - Konferenční příspěvek (zahraniční konf.)
Anderle, Milan - Čelikovský, Sergej
Sensor Fusion for simple walking robot using low-level implementation of Extended Kalman Filter.
IFAC-PapersOnLine. Volume 51, Issue 13. : 2nd IFAC Conference on Modelling, Identification and Control of Nonlinear Systems MICNON 2018. Amsterdam: Elsevier, 2018, s. 43-48. ISSN 2405-8963.
[Second IFAC Conference on Modelling, Identification and Control of Nonlinear Systems. Guadalajara (MX), 20.06.2018-22.06.2018]
Grant CEP: GA ČR(CZ) GA17-04682S
Institucionální podpora: RVO:67985556
Klíčová slova: Filtering and smoothing * Digital implementation * Walking robot
Obor OECD: Automation and control systems

The main aim of this paper depicts in design and implementation of the Extended
Kalman 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
measurement. 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.
Trvalý link: http://hdl.handle.net/11104/0285102