AI Summary & Key Takeaways
AI InsightAs a result of the analysis, the average errors of RTK/GNSS, tactical-grade IMU, and low-cost IMU are 0.58, 0.60, and 4.24 degrees, respectively.
📌 3 Key Takeaways
Abstract
Nowadays, autonomous vehicles (AVs) are employed for a wide range of jobs, including spraying, harvesting, and planting. For AVs to navigate autonomously, accurate heading knowledge of the vehicle is essential. Sensors such as the global navigation satellite system (GNSS) and inertial measurement unit (IMU) are used on AVs to produce heading information. Dual-frequency and RTK-capable systems with multiple antennas are used to increase the heading accuracy of GNSS. For IMUs, heading accuracy is directly related to the quality of the sensors, so high accuracy is achieved with expensive IMUs. However, with the development of micro-electro-mechanical system (MEMS) technology, studies are also being carried out on low-cost IMU solutions. In this study, the heading performances of three different sensors, a low-cost RTK/GNSS with multiple antennas, a tactical-grade IMU, and a low-cost MEMS IMU, were tested. An unmanned ground agricultural vehicle (UGAV) designed for spraying was driven on a line, and the data of the sensors mounted on the UGAV were collected. Heading accuracy was also examined according to the distance between the antennas of the RTK/GNSS system. As a result of the analysis, the average errors of RTK/GNSS, tactical-grade IMU, and low-cost IMU are 0.58, 0.60, and 4.24 degrees, respectively.