2013 International Conference on Unmanned Aircraft Systems (ICUAS), 2013
This paper presents a simple and easy to implement sensor data fusion algorithm, using a Kalman f... more This paper presents a simple and easy to implement sensor data fusion algorithm, using a Kalman filter (KF) in a loosely coupled scheme, for estimation of the velocity and position of an object evolving in a three dimensional space. A global positioning system (GPS) provides the position measurement while the velocity measurement is taken from the optical flow sensor, finally, the inertial navigation system (INS) gives the acceleration, which is considered as the input of the system. Real time experimental results are shown to validate the proposed algorithm.
2013 International Conference on Unmanned Aircraft Systems (ICUAS), 2013
This paper presents a simple and easy to implement sensor data fusion algorithm, using a Kalman f... more This paper presents a simple and easy to implement sensor data fusion algorithm, using a Kalman filter (KF) in a loosely coupled scheme, for estimation of the velocity and position of an object evolving in a three dimensional space. A global positioning system (GPS) provides the position measurement while the velocity measurement is taken from the optical flow sensor, finally, the inertial navigation system (INS) gives the acceleration, which is considered as the input of the system. Real time experimental results are shown to validate the proposed algorithm.
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Papers by Diego Mercado