Development of IMU and GPS applied ground coordinate system platform for agricultural robots

The desired yield in the outputs realized in precision agriculture activities is directly related to the positioning processes. It covers the basis of autonomous agricultural machinery in agricultural activities by creating a coordinate system on the agricultural area with the aim of efficient use of the agricultural area in sowing, planting, fertilizing, spraying and harvesting processes, minimizing labor, time and material costs. As a method, the use of autonomous systems in agricultural activities is increasing. The most important example is the automatic steering system that can be integrated into tractors. Automatic steering and autonomous systems are based on positioning processes and work on an electronic and software basis. With this approach, which creates an interdisciplinary need, the study of an electronic and software-based terrestrial coordinate system platform in agricultural activities in our country will be the first. GPS-based systems used for positioning on the basis of the study are quite common, but are also used in agricultural activities. However, in GPS-based systems, singular use cannot be preferred due to both cost and positioning errors. In the planned process, the location calculation process will be carried out by performing the terrestrial coordinate system platform, GPS assisted error correction processes, creating a closed circuit coordinate system and moving system coordinate system comparison measurements. Spraying and fertilizing will be used primarily in line with the sensitivity in location calculations. If the measurements obtained are considered sufficient, it can also be used in sowing, planting and harvesting processes. By designing the system in a modular structure, it is aimed to make it usable in all electrically mobile agricultural machines. When the location information obtained from the Sensor Fusion system developed on the mobile robot and the RTK GPS were evaluated, an average deviation of 0.11 m was determined. According to the deviation values of the position information obtained from both systems, the RMSE (Mean Square Root Deviation) was determined as 0.13 m.