DESIGN AND PROTOTYPE DEVELOPMENT OF ROBOTIC ARM FOR HARVESTING OF FRUITS AND VEGETABLES
The agricultural sector faces numerous challenges, including limited labor availability, rising costs driven by supply and demand dynamics, and the difficulty of operating in remote, infrastructure-deficient areas such as deserts. Additionally, manual harvesting processes are often time-consuming, impractical during holidays or crises, and lack detailed statistical data on harvested yields. The integration of solar energy with robotic systems presents an innovative solution to these challenges by providing a sustainable, off-grid power source for agricultural automation. This research focuses on the development of a solar-powered robotic arm designed to automate fruit and vegetable harvesting. By reducing reliance on manual labor, minimizing harvesting time, and utilizing clean energy sources, the proposed system addresses critical inefficiencies in traditional agricultural practices. The robotic arm prototype was carefully designed, and the materials were selected based on specific considerations. The prototype was evaluated in a controlled laboratory environment using artificial crop models that simulate the size, texture, color and fragility of real produce. The system achieved a harvesting accuracy of 89.6% and an average energy efficiency of 84.6%. Economically, the system demonstrated a positive Return on Investment (ROI) of 25.58% per year, enabling cost recovery within four years. These findings highlight the potential of solar-powered robotic systems to transform agriculture, particularly in remote and labor-constrained regions.
Authors
- Emad M. Ahmed (ORCID: https://orcid.org/0000-0001-7828-7556)
- A. T. Jailany
- A. ِA. Ali
Institutions
- Ministry of Water Resources and Irrigation (EG)
- Egypt-Japan University of Science and Technology (EG)
- Alexion Pharma (Switzerland) (CH)
Publication Details
- Journal
- Misr journal of agricultural engineering
- Published
- 2025-12-04
- DOI
- https://doi.org/10.21608/mjae.2025.436658.1168
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00