The objective of this research was to explore the use of data information of a low-cost IMU to provide an attitude angle with acceptable accuracy for agricultural robot navigation. This work was an attempt to create attitude angle estimation system via sensor fusion method based on gyroscope and accelerometer in this low-cost IMU. The used algorithm processed and integrated the data from triple gyroscope and tri-axis accelerometer using a low-pass filter and Kalman filter. Under this algorithm, experiment data showed that the estimation precision was improved effectively.

There is a growing concern by governments, retailers and consumers about the safety and quality of food. Because products are resourced on a on a global scale it becomes important that the origin of the products as well as all the treatments during production can be traced and that the production methods can be verified as good agricultural practices (GAP). This also includes considerations for the environment and sustainability.

The field of precision agriculture increasingly utilize and develop robotics for various applications, many of which are dependent on high accuracy localization and attitude estimation. Special attention has been put towards full attitude estimation by low-cost sensors, in relation to the development of an autonomous field robot. Quaternions have been chosen due to its continuous nature, and with respect to applications in the pipeline with on other platforms.