Session

Mechatronics, Robotics and System Engineering

Description

The Accelerometer and Gyroscope modules used for measuring the orientation of the quadcopter usually generate noisy signals which directly affect the control strategies. The high speed motors used in quadcopters cause high noise levels which makes the real time control almost impossible. In this work the Kalman filter is applied to the noisy measurements obtained from accelerometer and gyroscope modules. The measurements are conducted for two cases: Motors stopped, and Motors activated at high speed. The Kalman filtering is applied separately for each measurement and the obtained results show noticeable improvement in noise level for two cases. The joint implementation from accelerometer and gyroscope modules is also conducted in order to optimize the predicted signal levels. The results show that the proposed Kalman filtering method can be used in real time measurement of quadcopter orientation, also in the case of low-cost measurement modules.

Keywords:

Kalman Filter, Noise Reduction, Quadcopter Sensor Modules, Noisy Accelerometer

Proceedings Editor

Edmond Hajrizi

ISBN

978-9951-550-10-9

First Page

29

Last Page

33

Location

Durres, Albania

Start Date

7-11-2015 9:00 AM

End Date

7-11-2015 5:00 PM

Included in

Robotics Commons

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Nov 7th, 9:00 AM Nov 7th, 5:00 PM

Noise reduction in Quadcopter Accelerometer and Gyroscope Measurements based on Kalman filter

Durres, Albania

The Accelerometer and Gyroscope modules used for measuring the orientation of the quadcopter usually generate noisy signals which directly affect the control strategies. The high speed motors used in quadcopters cause high noise levels which makes the real time control almost impossible. In this work the Kalman filter is applied to the noisy measurements obtained from accelerometer and gyroscope modules. The measurements are conducted for two cases: Motors stopped, and Motors activated at high speed. The Kalman filtering is applied separately for each measurement and the obtained results show noticeable improvement in noise level for two cases. The joint implementation from accelerometer and gyroscope modules is also conducted in order to optimize the predicted signal levels. The results show that the proposed Kalman filtering method can be used in real time measurement of quadcopter orientation, also in the case of low-cost measurement modules.