Design and implementation of sensor data fusion for an autonomous quadrotor

Abstract

This paper describes the design and integration of the instrumentation and sensor fusion that is used to allow the autonomous flight of a quadrotor. A comercial frame is used, a mathematical model for the quadrotor is developed and its parameters determined from the characterization of the unit. A 9 degrees of freedom Inertial Measurement Unit (IMU) equipped with a barometer is calibrated and added to the platform. Sensor fusion is done by two modified Extended Kalman Filters (EKF): one combining data provided by IMU and the other also including the information provided by GPS. A reliable estimation of the state variables is obtained. Three states representing systematic bias in the accelerometer measurements are also added to the EKF, which improves the inertial estimation of the position. A stable autonomous platform is achieved