A Low-Cost Integrated Positioning System of GPS and Inertial Sensors for Autonomous Agricultural Vehicles

A low-cost integrated positioning system, consisting of a Garmin GPS and a set of solidstate inertial sensors, was developed for autonomous agricultural vehicle applications. Based on a position-velocity-attitude (PVA) model of the vehicle, a PVA model-based Kalman filter was designed to integrate data from all sensors to provide accurate and robust vehicle positioning data. This integrated positioning system was evaluated in different test sites. An RTK-DGPS receiver was used to provide reference measurements. Test results showed that the maximum positioning error was 0.50 m while the vehicle was traveling on a known path (determined based on static RTK-DGPS measurements) on a paved road nearby buildings and partially under trees. When the vehicle was traveling on open field, the maximum error was 0.30 m compared with RTK-DGPS dynamic measurement. In both cases, the redundant positioning information was fused and the update rate was increased to 50 Hz while the GPS receiver updated its positioning reading at 1 Hz. The test results also demonstrated that, the integrated system could estimate the vehicle position accurately with a temporary GPS signal outage (up to 30 s). The accuracy of this low-cost integrated positioning system can meet most tasks in precision farming applications.