Abstract: The development of robotic systems for automated fruit harvesting in intensive orchards has emerged as a critical response to labor shortages, high production costs, and the need for efficiency in modern agriculture. This study presents the kinematic modeling and design of a robotic manipulator system integrated into a mobile platform with an articulated lift mechanism, dual manipulators, and compliant gripping devices equipped with vision-based perception. The proposed system was modeled and validated through simulation in SolidWorks, enabling analysis of workspace coverage, kinematic stability, and motion optimization. Results indicate that the dual-manipulator configuration achieved a harvesting rate of up to 12 trees per hour, reducing the average fruit cycle time to less than seven seconds while lowering fruit loss to 14.5%, compared to over 30% in manual harvesting. The gripping device demonstrated a success rate of 94% with safe detachment forces between 2.5 and 3.5 N, ensuring minimal fruit damage and consistent quality. The lift mechanism provided stable vertical translation with minimal lateral deflection, supporting precise manipulator operation. Overall, the study highlights the potential of robotic manipulators to enhance productivity, safety, and sustainability in orchard management, while outlining future directions for field implementation, adaptive vision algorithms, and autonomous navigation.

Nurbibi Imanbayeva, Bekzat Amanov, Aiman Nurmaganbetova, Arman Moldashev, Akbayan Aliyeva and Sulukul Dauletbekova. “Kinematic Modeling and Design of a Robotic Manipulator System for Automated Fruit Harvesting in Intensive Orchards”. International Journal of Advanced Computer Science and Applications (IJACSA) 16.11 (2025). http://dx.doi.org/10.14569/IJACSA.2025.0161131

@article{Imanbayeva2025,
title = {Kinematic Modeling and Design of a Robotic Manipulator System for Automated Fruit Harvesting in Intensive Orchards},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2025.0161131},
url = {http://dx.doi.org/10.14569/IJACSA.2025.0161131},
year = {2025},
publisher = {The Science and Information Organization},
volume = {16},
number = {11},
author = {Nurbibi Imanbayeva and Bekzat Amanov and Aiman Nurmaganbetova and Arman Moldashev and Akbayan Aliyeva and Sulukul Dauletbekova}
}