Intelligent Fruit-Picking Robot Using Convolutional Vision and Kinematic Control for Automated Harvesting
Imanbayeva N.S. Amanov B.O. Altayeva A.B. Ashimova D.K.
January 2026Science and Information Organization
International Journal of Advanced Computer Science and Applications
2026#17Issue 1304 - 314 pp.
This study presents the design, development, and evaluation of an intelligent fruit-picking robot that integrates convolutional vision, adaptive gripping mechanisms, and kinematic control to enable automated harvesting in diverse orchard environments. The proposed system combines a dualmanipulator platform with an extendable scissor-lift mechanism to achieve wide workspace coverage, allowing efficient access to fruits located at varying canopy heights. A deep learning-based recognition module, trained on a Mixed Fruit Dataset, is employed to detect and classify fruits under challenging conditions characterized by occlusions, variable illumination, and dense foliage. Visualization of feature activations confirms that the model effectively focuses on discriminative fruit regions, supporting precise alignment of the end-effector during grasping. The adaptive gripper, designed with compliant materials and multi-configuration geometry, ensures gentle handling across fruits of different shapes and sizes, minimizing mechanical damage. Experimental evaluations demonstrate that the system performs reliably across multiple fruit species, achieving accurate identification, robust segmentation, and stable manipulation in real-field scenarios. The integrated results highlight the robot’s potential to reduce labor dependency, improve harvesting efficiency, and support scalable automation in mixed-crop orchards. Future work will address enhancements in real-time processing, autonomous navigation, and cross-species generalization to advance fully autonomous orchard operations.
adaptive gripper , agricultural robotics , automated harvesting , computer vision , deep learning , Fruit-picking robot , kinematic control , Mixed Fruit Dataset , orchard automation , transformer model
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Joldasbekov Institute of Mechanics and Engineering, Almaty, Kazakhstan
International Information Technology University, Almaty, Kazakhstan
Zhanibekov University, Shymkent, Kazakhstan
Joldasbekov Institute of Mechanics and Engineering
International Information Technology University
Zhanibekov University
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