Design and Development of an Autonomous Guided Mobile Manipulator for Precision Tomato Picking and Harvesting

Abstract

This project aims to develop a prototype of an Autonomous Guided Mobile Manipulator for precision tomato harvesting to address labor shortages in agriculture. The system integrates sensing, mobility, vision (ESP32-CAM), and manipulation (5 DOF robotic arm). Experimental results showed a vision detection accuracy of 90% in daylight and an integrated harvest success rate of 68-75% in semi-field conditions. The project demonstrates the feasibility of affordable robotic harvesters in agricultural modernization.

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