Abstract:
This paper presents mathematical modeling,
implementation and experimentation results of Extended
Kalman filter (EKF) implemented on existing flight control
algorithm which is used to control multi-rotor unmanned aerial
vehicles such as quadcopters, hexacopters, and octocopters.
Purpose of implementing the EKF is to improve flight
performance and reliability of the vehicles during its
autonomous navigation which may include automatic take-off
landing, waypoint navigation, and to improve the robustness for
wind disturbances at the same time. Initially vision positioning
data were used as a ground truth to validate the EKF outputs.
Then the filter is tested in real-time using a quadcopter and
experimental results were presented and compared with raw
sensor data to evaluate system performance.
Citation:
Somasiri, J.A.A.S., Chandima, D.P., & Jayasekara, A.G.B.P. (2018). Extended Kalman filter based autonomous flying system for quadcopters. In R. Samarasinghe & S. Abeygunawardana (Eds.), Proceedings of 2nd International Conference on Electrical Engineering 2018 (pp. 130-137). Institute of Electrical and Electronics Engineers, Inc. https://ieeexplore.ieee.org/xpl/conhome/8528200/proceeding
