Autonomous guidance for rice transplanting using global positioning and gyroscopes
There is an increasing trend in Japan towards consolidating, and thus enlarging, paddy fields. Because this demands more efficient operations, the authors developed an automated six-row rice transplanter. It employs a real-time kinematic global positioning system (RTKGPS) for precise positioning, fiber optic gyroscope (FOG) sensors to measure direction, and actuators to control steering, engine throttle, clutch, brake, etc. The RTKGPS achieves 2cm precision at 10Hz data output rate, and the FOG sensors are employed to maintain vehicle inclination. RTKGPS position data, influenced by vehicle inclination, are corrected by the FOG sensor data. FOG sensor drift is corrected by referring to the position data. To eliminate the influence of drift, deviation from the desired path, calculated from yaw angle and vehicle speed, is first compared with the deviation calculated using GPS data. Heading angle drift is then calculated. An experiment was conducted two days after flooding the field. The authors used a simple proportional steering controller. Root mean square deviation from the desired straight path after correcting for the yaw angle offset was approximately 5.5cm at a speed of 0.7m/s. The maximum deviation from the desired path is less than 12cm which does not include the first 2m after starting operation. Transplanting a field was completed in 15min. The autonomous operation was accurate enough for the rice transplanting. However, the authors could not obtain enough accuracy for spraying or mechanical weeding operations after rice transplanting because the vehicle must travel between the crop rows. For this to occur, it is necessary to improve the turn control algorithm and steering controller to obtain more precise operations.
rice transplanter paddy fields rtkgps fog automated operation