Design and performance evaluation of a solar powered remote controlled robot for precision seed planting

Abstract The increasing demand for sustainable agricultural mechanization has accelerated the development of precision and energy-efficient planting systems. This study presents the design, optimization, and performance evaluation of a solar-powered remotely controlled robot for precision seed planting. The robotic platform integrates a photovoltaic energy system, an electric seed-metering mechanism, and an electronically controlled seed-depth adjustment unit to achieve accurate seed placement while minimizing energy consumption. The system was experimentally evaluated at four robot forward speeds (0.42–1.60 km h −1 ) and four target seed spacings (10–25 cm). Results showed high seed placement accuracy ranging from 98.08% to 98.80%, while the miss and multiple indices remained below 2% and 2.5%, respectively. Optimal metering performance was obtained at robot speeds of 0.82–1.20 km h −1 . The seed-depth adjustment mechanism exhibited a strong linear relationship between motor rotations and penetration depth (R 2 = 0.9996), ensuring precise depth control. Energy analysis indicated low power consumption (0.048–0.084 kWh) and a solar power supply ratio (95–167%). These findings demonstrate that integrating solar energy with wirelessly controlled agricultural robotics can improve planting precision while enhancing energy efficiency and environmental sustainability in precision farming systems.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2026-09-15
DOI
https://doi.org/10.1038/s41598-026-68946-0
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

Design and performance evaluation of a solar powered remote controlled robot for precision seed planting

Ayman Eldesoukey, Z. M. Omara, Ismail Abdelmotaleb, El-Keway Abdelfattah et al.
Scientific Reports
Smart Agriculture and AI
article

Design and performance evaluation of a solar powered remote controlled robot for precision seed planting

Ayman Eldesoukey, Z. M. Omara, Ismail Abdelmotaleb, El-Keway Abdelfattah, Shimaa Aboharg, Noureldin Sharaby
article en

Abstract

Abstract The increasing demand for sustainable agricultural mechanization has accelerated the development of precision and energy-efficient planting systems. This study presents the design, optimization, and performance evaluation of a solar-powered remotely controlled robot for precision seed planting. The robotic platform integrates a photovoltaic energy system, an electric seed-metering mechanism, and an electronically controlled seed-depth adjustment unit to achieve accurate seed placement while minimizing energy consumption. The system was experimentally evaluated at four robot forward speeds (0.42–1.60 km h −1 ) and four target seed spacings (10–25 cm). Results showed high seed placement accuracy ranging from 98.08% to 98.80%, while the miss and multiple indices remained below 2% and 2.5%, respectively. Optimal metering performance was obtained at robot speeds of 0.82–1.20 km h −1 . The seed-depth adjustment mechanism exhibited a strong linear relationship between motor rotations and penetration depth (R 2 = 0.9996), ensuring precise depth control. Energy analysis indicated low power consumption (0.048–0.084 kWh) and a solar power supply ratio (95–167%). These findings demonstrate that integrating solar energy with wirelessly controlled agricultural robotics can improve planting precision while enhancing energy efficiency and environmental sustainability in precision farming systems.

Scientific ReportsVol. 16(1)
Kafrelsheikh University (EG), Agricultural Genetic Engineering Research Institute (EG)
Zero hunger
Openalex Percentile: Top 12%
Smart Agriculture and AI
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.