食用菌采收机器人研究进展与展望

Research Progress and Outlook on Edible Mushroom Harvesting Robots

摘要:

在食用菌产业规模化与工厂化发展的背景下,采收环节对人工依赖程度高,已成为制约食用菌生产全流程自动化的瓶颈。针对国内主要栽培品种———香菇、金针菇、双孢菇、平菇等,系统梳理了棒栽、床栽、袋栽、瓶栽等不同栽培模式下采收作业环境特点,分析了各类食用菌典型生产模式下的作业约束及技术需求。综述了国内外食用菌采收机器人研究及其产品化进展,对比分析了国外基于标准化栽培体系的自动化技术路线与国内面向多品种、非结构化环境的技术特点,总结了国内外食用菌采收技术差异与发展启示。围绕食用菌采收机器人末端执行器、感知、运动平台与系统集成、具身智能技术应用等方面关键技术,重点评述了夹持式、吸附式、切割式及仿生柔性末端执行器的发展现状,以及深度学习、立体视觉和多模态信息融合技术在成熟度识别与目标定位中应用的发展趋势。讨论了固定式、移动式和轨道式平台在狭窄高湿栽培环境中的适应性及系统集成特点。总结分析当前食用菌采收机器人仍存在感知鲁棒性不足、末端执行器兼容性差、作业效率低和经济性差等技术难点。最后,提出了加强栽培模式标准化与农机农艺融合,发展感知决策控制一体化的具身智能采收系统,构建采收、切根、分级等环节协同的自动化生产线等未来技术发展方向。

Abstract:

Against the backdrop of large-scale and industrialized development of the edible mushroom industry, harvesting remains highly dependent on manual labor and has become a key bottleneck restricting full-process automation. Focusing on major cultivated species in China, such as shiitake mushroom, enoki mushroom, button mushroom, and oyster mushroom, the characteristics of harvesting environments under different cultivation modes were systematically reviewed, including log cultivation, bed cultivation, bag cultivation, and bottle cultivation, and the operational constraints and technical requirements associated with typical production systems were analyzed. The research progress and commercialization of edible mushroom harvesting robots at home and abroad were comprehensively reviewed. The automated technical routes adopted in foreign countries under standardized cultivation systems were compared with the domestic technical features oriented toward multiple species and unstructured environments, and the differences and implications of domestic and international harvesting technologies were summarized. Key technologies of edible mushroom harvesting robots were discussed, including end-effectors, perception, mobile platforms, system integration, and embodied intelligence. Particular attention was given to the development of gripping, suction, cutting, and bio-inspired flexible end-effectors, as well as to the application trends of deep learning, stereo vision, and multimodal information fusion in maturity recognition and target localization. The adaptability and integration characteristics of fixed, mobile, and rail-guided platforms in narrow and humid cultivation environments were also examined. Current technical challenges were summarized, including insufficient perception robustness, poor compatibility of end-effectors, low operational efficiency, and weak economic feasibility. Finally, future prospects were proposed from three aspects: strengthening the standardization of cultivation modes and the integration of agronomy with agricultural machinery, developing embodied intelligent harvesting systems integrating perception, decision-making, and control, and constructing automated production lines that coordinated harvesting, root cutting, grading, and other postharvest processes, so as to provide theoretical support and technical references for the intelligent upgrading of China’s edible mushroom industry.