Facultad Regional Córdoba

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Subject: search.filters.subject.Sensor fusion

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    IMU-and exteroceptive sensor-based fusión for UAV control.
    (IEEE Xplore., 2017) Pérez Paina , Gonzalo; Pucheta , Martín Alejo; Paz, Claudio
    A quadrotor is an unmanned aerial vehicle (UAV) popular for its low-cost and broad range of applications, like in spection, surveillance, cinematographic filmation, among others. Most of these applications are easily performed if the quadrotor is able to flight autonomously, which can be achieved using a feedback control loop. In order to be close the loop, the UAV state has to be estimated using the information of the on-board sensors. This work presents an IMU- and exteroceptive sensor- based fusion approach for state estimation to be used in a quadrotor control loop. The presented results are based on simulations using a dynamic model of the quadrotor, in which the performed estimation is used as feedback vector instead of the model true output. These results show that the proposed estimation approach is accurate enough to control the quadrotor and perform typical paths, like a circle and a square path.
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    Validation of an IMU-camera fusion algorithm using an industrial robot.
    (Jornadas Argentinas de Robótica, 2017) Pérez Paina , Gonzalo; Paz , Claudio; Pucheta, Martín Alejo; Bianchini, Bruno; Martínez , Fernando; Nievas , Martín
    The integration of down-looking camera with an in ertial measurement unit (IMU) sensor makes possible to provide a lightweight and low-cost pose estimation system for unmanned aerial vehicles (UAVs) and micro-UAVs (MAVs). Recently, the authors developed an algorithm for IMU and exteroceptive sensor fusion filter for position and orientation estimation. The aim of the estimation is to be used in the outer control loop of an UAV for position control. This work presents an experimental set up to test that algorithm using an industrial robot to produce accurate planar trajectories as a safe alternative to testing the algorithm on real UAVs. The results of the IMU-camera fusion estimation for linear positions and linear velocities show an error admissible to be integrated on real UAVs. Index Terms—sensor fusion, inertial measurement unit, monoc ular camera, industrial robot, error-state Kalman f