Solar-Powered Seeding Robot Achieves 98.8% Seed Positioning Accuracy
Global agriculture is under increasing pressure to feed nearly 10 billion people by 2050 while reducing environmental impact and addressing shrinking rural labor. Traditional mechanization largely depends on fossil fuels, leading to soil compaction, greenhouse gas emissions, and economic barriers for small and medium farms.
Precision seeding is critical for crop establishment and yield, but conventional ground-driven seed metering systems suffer from slippage and synchronization errors that reduce accuracy. Electric seed meters improve spacing precision, and solar-powered agricultural robots offer a path to sustainable operation.
However, seeding robots remain underexplored, and research integrating solar power with precision seed metering is still limited. This study addresses that gap by developing a solar-powered seeding robot and evaluating its performance under controlled conditions.
The robot's mechanical structure integrates several specialized subsystems for steering, propulsion, seeding, and depth control. Steering is achieved by a brushed DC motor driving a lead screw, with front-wheel chain transmission and limit switches ensuring synchronized, repeatable directional control. Propulsion comes from two 250 W DC motors powered by solar-charged batteries, transmitting torque to the rear wheels via spur gearboxes. Speed is regulated using pulse-width modulation and phase-locked loops, with encoder feedback maintaining stable low-speed operation and traction under varying loads.
The electric seeding unit uses encoder pulses as reference signals to synchronize the rotating seed plate with forward motion. A closed-loop control strategy adjusts the seed plate rotation to match travel speed based on encoder feedback, while an infrared sensor monitors each seed as it is discharged. The closed-loop control ensures precise synchronization between seed discharge and ground speed, minimizing miss and repeat indices. An Arduino microcontroller serves as the central control unit, and a 2.4 GHz wireless link allows an operator to remotely adjust speed, spacing, and seeding depth. Temperature sensors provide overheat protection. Seeding depth is controlled by a separate motor-driven lead screw mechanism that lifts and lowers the furrow opener. Power is supplied by a 100 W solar panel charging two 12 V batteries, with the solar supply ratio used as an energy balance indicator.
Preliminary trials identified a 35-degree seed plate inclination as optimal, yielding spacing closest to the target with the lowest variability. Speed calibration confirmed a strong linear relationship between motor voltage and forward speed. Feasibility analysis showed that lower speeds provide sufficient seeding time, while the combination of the highest speed and smallest spacing approaches a critical threshold, making the system more sensitive to vibration and soil irregularities. Seeding performance was most stable at medium speed and intermediate spacing. The miss and repeat indices remained low, with spacing accuracy between 98.08% and 98.80%. Statistical analysis confirmed that robot speed has the greatest impact on accuracy, followed by seed spacing. Wider spacing improved stability by reducing seeding frequency. The depth adjustment unit showed a strong linear relationship between motor rotation and penetration depth, confirming precise, repeatable depth control. Power consumption increased with speed under both no-load and load conditions. The solar supply ratio, defined as the ratio of solar energy to total energy consumption, ranged from 95% to 167%, indicating that the photovoltaic system can fully power the robot at medium speeds and partially at higher loads. The robot produces no direct field emissions during operation.
Under the tested operating conditions, spacing accuracy ranged from 98.08% to 98.80%, with miss and repeat indices below 2% and 2.5%, respectively. Optimal seeding occurred at forward speeds of 0.82 to 1.2 km/h, and wider spacing of 20 to 25 cm improved distribution consistency. The depth adjustment unit demonstrated precise, repeatable control, power consumption remained low at 48 to 84 W, and the solar supply ratio ranged from 95% to 167%. Future work should integrate autonomous navigation such as RTK-GNSS or machine vision, conduct area-based emission comparisons, extend the system to multi-row seeding, and validate solar and battery performance under field conditions. This research demonstrates the potential of solar-powered seeding robots to improve agricultural sustainability and efficiency.