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 2 cm precision at 10 Hz 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 5.5 cm at a speed
of 0.7 m/s. The maximum deviation from the desired path is less than 12 cm which does not include
the first 2m after starting operation. Transplanting a 10m×50m field was completed in 15 min. 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
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 ricetransplanter. 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 2 cm precision at 10 Hz data output rate, andthe FOG sensors are employed to maintain vehicle inclination. RTKGPS position data, influenced byvehicle inclination, are corrected by the FOG sensor data. FOG sensor drift is corrected by referringto the position data. To eliminate the influence of drift, deviation from the desired path, calculatedfrom 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 thefield. The authors used a simple proportional steering controller. Root mean square deviation fromthe desired straight path after correcting for the yaw angle offset was approximately 5.5 cm at a speedof 0.7 m/s. The maximum deviation from the desired path is less than 12 cm which does not includethe first 2m after starting operation. Transplanting a 10m×50m field was completed in 15 min. Theautonomous operation was accurate enough for the rice transplanting. However, the authors couldnot obtain enough accuracy for spraying or mechanical weeding operations after rice transplantingbecause the vehicle must travel between the crop rows. For this to occur, it is necessary to improve
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