Authors

Abstract

In Addressing the high labor costs and low efficiency in greenhouse tomato harvesting and packaging, this study designed a tomato-picking robotic system integrating machine vision, a multi-degree-of-freedom robotic arm, and automatic heat-sealing packaging. The system employs the YOLO algorithm for ripe tomato detection (95.2% success rate) and combines A* and TEB algorithms for path planning, achieving full automation from detection and picking to packaging. Experimental results indicate a single-fruit processing cycle of approximately 12.1 seconds, with a picking success rate of 90.8% and a packaging success rate of 98.3%, representing a roughly 30% efficiency improvement over manual labor. This system marks the first integrated picking and packaging operation, providing a viable technical solution for automated greenhouse tomato production.

Abstract in Chinese

本研究针对温室番茄采摘与包装劳动力成本高、效率低的问题，设计了一种集成机器视觉、多自由度机械臂与热封自动包装功能的番茄采摘机器人系统。系统采用YOLO算法实现成熟番茄识别（成功率95.2%），结合A*与TEB算法进行路径规划，实现从识别、采摘到包装的全流程自动化。实验结果表明，单果处理周期约12.1秒，采摘成功率90.8%，包装成功率98.3%，相比人工效率提升约30%。本系统首次实现采摘与包装一体化作业，为温室番茄自动化生产提供可行技术方案。