MODEL AND ALGORITHMS FOR DETERMINING THE LOCATION AND POSITION OF AGRICULTURAL MACHINERY DURING THE MOVEMENT

• Main Authors: Andrii Podorozhniak, Oleksii Balenko, Valentyn Sobol
• Format: Article
• Language: English
• Published: Kharkiv National University of Radio Electronics 2021-06-01
• Series: Сучасний стан наукових досліджень та технологій в промисловості
• Subjects: autonomous control system; agricultural machinery; inertial navigation; odometry; satellite navigation
• Online Access: https://itssi-journal.com/index.php/ittsi/article/view/275
• ISSN: 2522-9818; 2524-2296

The subject of research is the navigation subsystem of autonomous control system to determine the location and position of agricultural machinery during the movement. The purpose of the work is to develop and research model and algorithms to determine the location and position of mobile agricultural machinery using a physical model. The following tasks are solved in the article: development of agricultural machinery physical model to collect information from sensors during movement, further development and research of applicability of algorithms for location and position determination. The following methods are used: methods of mathematical statistics, methods of information systems theory and data processing, methods of random signals filtration. The following results were obtained: during research, the agricultural machinery physical model to collect information from sensors during movement was created. The model includes a GPS receiver, an accelerometer, gyroscope and infrared encoders, to count the rotation of the wheels, as well as its own four wheelbase of agricultural machinery. The modernized GPS coordinate filtration algorithm using a geochex algorithm is proposed, which according to several successively obtained GPS coordinates calculates the hash received coordinates; if the coordinates have the same hash, it can be argued that the vehicle is in the segment of the area that corresponds to this hash. To determine the physical model position during the movement data from the accelerometer and the gyroscope was processed using Savitzky-Golay and Madgwick filters. With the use of wheels’ rotation data, the odometric algorithms for movement and location determining of the agricultural machinery physical model in motion were implemented. Conclusions: to improve the accuracy of estimating the location and position agricultural machinery, algorithms complexation of indicators from different navigation systems should be used to reduce the total error. Research results can be applied in the development of new and modifications of existing navigation subsystems of agricultural machinery autonomous control systems.