Comparison of Four Different Methods for Agricultural Positioning Using GPS and IMU

Abstract

In this research, four different positioning methods were compared in order to evaluate their accuracy, using a remotely controlled robot on a specific route. These methods included: using a single GPS module, combining the data from three GPS modules, using an Inertial Measurement Unit (IMU), and GPS/IMU data fusion. The comparison of these four methods showed that GPS/IMU data fusion along with a Kalman filter was the most precise method, having a root mean square error of 23.4cm. Integrating the data acquired simultaneously from three GPS modules with fixed and equally spaced position and far enough from each other, had a root mean square error of 31.3cm was the second most precise method. . Also analysis of the IMU data showed that due to cumulative errors, it was not a suitable method using a single IMU for positioning.

Keywords

• Global positioning system
• inertial measurement unit
• Data fusion
• Kalman filter