Validation of an IMU-camera fusion algorithm using an industrial robot.
Date
2017
Journal Title
Journal ISSN
Volume Title
Publisher
Jornadas Argentinas de Robótica
Abstract
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
Description
Keywords
Sensor fusion, Inertial measurement unit, Monocular camera, Industrial robot, Error-state Kalman filter
Citation
JAR 2017- IX Jornadas Argentinas de Robótica 15-17 de noviembre, córdoba Argentina.
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Creative Commons license
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