Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
489283 | Procedia Computer Science | 2015 | 6 Pages |
This article presents a practical application of the Kalman filter by implementing a sensor array in a Bebop Parrot drone in order to detect objects within a determined rank to reduce the background noise in the obtained measurements. The effect of the relationship between the measurement taken by the sensors and the effectiveness of the background noise reduction using the Kalman filter was studied, thus reducing the variation of the sensor measurement. The objective of this implementation can help improve the teaching of the application of Kalman filter. Information readings are performed by the HC-SR04 ultrasonic sensors connected to the data acquisition board Arduino Yun, which interprets the electronic pulses to get the distance in meters and, at the same time, send them via serial port to a Raspberry Pi board; this board implements the Kalman filter sending the data via Wi-Fi to a computer connected to the network that allows visualizing the results of measurements and filter performance. The results obtained show the improvement of the data measurement by the distance sensors with the purpose of providing the drone with greater accuracy of data acquisition.