智能化农业装备学报（中英文）

农业机器人中的管理与采摘技术：现状、挑战与未来发展

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王得志 , 王延鑫 , 汪小旵 ^*^,^* , 施印炎 , 章永年

智能化农业装备学报（中英文） | 2025,6(2): 1-23

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智能化农业装备学报（中英文） | 2025 , 6 (2) : 1 -23

农业机器人中的管理与采摘技术：现状、挑战与未来发展

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王得志, 王延鑫, 汪小旵^*^,^*, 施印炎, 章永年

作者信息

南京农业大学工学院，江苏南京，210031

通讯作者:

^* 汪小旵，男，1968年生，安徽安庆人，博士，教授；研究方向为农业机器人、农业装备电动化智能化控制。E-mail：wangxiaochan@njau.edu.cn

作者简介:

王得志，男，1998年生，山东烟台人，博士研究生；研究方向为农业机器人。E-mail：2024212004@stu.njau.edu.cn

Management and harvesting technologies in agricultural robotics: Current status, challenges and future developments

Dezhi WANG, Yanxin WANG, Xiaochan WANG, Yinyan SHI, Yongnian ZHANG

Affiliations

College of Engineering, Nanjing Agricultural University, Nanjing 210031, China

Corresponding Author:

^* WANG Xiaochan, E-mail: wangxiaochan@njau.edu.cn

WANG Dezhi, E-mail: 2024212004@stu.njau.edu.cn

出版时间: 2025-05-15 doi: 10.12398/j.issn.2096-7217.2025.02.001

文章导航

摘要

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农业机器人是现代农业发展的重要方向，已经成为全球农业装备技术竞争的战略高地。作为特种机器人技术的重要分支，农业机器人的核心结构包括信息感知系统、决策控制系统、作业执行机构和自主移动平台，经历了从半自动化到智能化的多个发展阶段。为了准确把握农业机器人的研究现状和发展方向，本研究阐述了农业机器人的概念、国内外发展政策及技术背景。农业管理机器人和采摘机器人是农业机器人领域的两大核心方向，管理机器人通过实时监测作物生长状况及环境条件，实现对生产管理操作的精准调控。采摘机器人则通过自主导航、智能识别和精准控制技术，自动执行作物采摘任务。本研究重点探讨了信息采集机器人、授粉机器人、除草机器人、植保机器人和打叶整枝机器人等管理类机器人，以及水果、蔬菜、花卉和茶叶等采摘机器人的前沿进展、技术瓶颈和关键突破方向。结合我国农业的具体需求和特点，深入分析了农业机器人的技术瓶颈和关键突破方向，包括精准信息感知和识别、实时数据处理与智能决策、自适应底盘路径规划与自主导航、作业执行机构设计与精准作业控制等。展望农业机器人将在作物管理、病虫害防治和采摘等领域实现广泛应用，加速迈向智能化、精准化和自主化阶段。依托先进技术解决农业生产中的挑战，推动农业劳动力优化、生产效率提升，成为智慧农业的关键支撑。

关键词

农业机器人 / 管理技术 / 采摘技术 / 智慧农业 / 精准作业

Abstract

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Agricultural robots constitute a crucial trajectory in the evolution of modern agriculture, and has emerged as a focal point of strategic global competition in agricultural equipment technology. As a specialized domain within robotics, agricultural robots are fundamentally composed of an information perception system, decision-making control system, operation execution mechanism, and autonomous mobile platform, having gone through multiple development stages from semi-automation to intelligence. This paper aims to provide a precise understanding of the contemporary research landscape and future trajectories of agricultural robots by delineating their conceptual framework, reviewing relevant national and international development policies, and outlining the underpinning technical background. Agricultural management robots and picking robots are two core directions in the field of agricultural robotics. Management robots achieve precise control of production management operations through real-time monitoring of crop growth parameters and environmental conditions. Picking robots, on the other hand, automatically perform crop picking tasks through autonomous navigation, intelligent recognition and precise control technology. This paper focuses on cutting-edge progress, technical bottlenecks, and key breakthrough directions concerning various management robots, including those for information acquisition, pollination, weed control, plant protection, leaf pruning and intelligent irrigation systems, as well as picking robots dedicated to fruits, vegetables, flowers, and tea. Considering the distinct requirements and characteristics of China's agriculture, this analysis critically analyzed the technological bottlenecks and key breakthrough directions of agricultural robots, including precise information perception and recognition, real-time data processing and intelligent decision-making, adaptive chassis path planning and autonomous navigation, and operational actuator design and precise operational control. It is envisioned that agricultural robots will be widely applied in the fields of crop management, precision irrigation, pest control and picking, thereby accelerating the the evolution of agriculture towards a more intelligent, precise, and autonomous paradigm. Relying on advanced technology to address challenges in agricultural production, it will promote the optimization of agricultural workforce and the improvement of production efficiency, and server as a foundational pillar for the realization of smart agriculture.

Key words

agricultural robot / management technology / harvesting technology / smart agriculture / precise operation

引用本文

王得志, 王延鑫, 汪小旵, 施印炎, 章永年. 农业机器人中的管理与采摘技术：现状、挑战与未来发展. 智能化农业装备学报（中英文）, 2025 , 6 (2) : 1 -23 . DOI: 10.12398/j.issn.2096-7217.2025.02.001

Dezhi WANG, Yanxin WANG, Xiaochan WANG, Yinyan SHI, Yongnian ZHANG. Management and harvesting technologies in agricultural robotics: Current status, challenges and future developments[J]. Journal of Intelligent Agricultural Mechanization, 2025 , 6 (2) : 1 -23 . DOI: 10.12398/j.issn.2096-7217.2025.02.001

基金

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国家重点研发计划项目(2023YFD2000304)
江苏省重点研发计划项目(BE2021302)
江苏省农业科技自主创新资金项目(CX（21）2006)

参考文献

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文献

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参考文献引证文献

排序方式：

[1]

刘成良，贡亮，苑进，等．农业机器人关键技术研究现状与发展趋势[J]．农业机械学报，2022，53（7）：1-22，55.

LIU Chengliang, GONG Liang, YUAN Jin, et al. Current status and development trends of agricultural robots [J]. Transactions of the Chinese Society for Agricultural Machinery, 2022, 53(7): 1-22, 55.

[2]

赵春江，范贝贝，李瑾，等．农业机器人技术进展、挑战与趋势[J]．智慧农业（中英文），2023，5（4）：1-15.

ZHAO Chunjiang, FAN Beibei, LI Jin, et al. Agricultural robots: Technology progress, challenges and trends [J]. Smart Agriculture, 2023, 5(4): 1-15.

[3]

MUELLER-SIM T, JENKINS M, ABEL J, et al. The Robotanist: A ground-based agricultural robot for high-throughput crop phenotyping [C]. IEEE, 2017.

[4]

SHAFIEKHANI A, KADAM S, FRITSCHI F, et al. Vinobot and vinoculer: Two robotic platforms for high-throughput field phenotyping [J]. Sensors, 2017, 17(1): 214.

[5]

ZHANG Z, KAYACAN E, BENJAMIN T, et al. High precision control and deep learning-based corn stand counting algorithms for agricultural robot [J]. Autonomous Robots, 2020, 44(7): 1289-1302.

[6]

CUBERO S, MARCO-NOALES E, ALEIXOS N, et al. RobHortic: A field robot to detect pests and diseases in horticultural crops by proximal sensing [J]. Agriculture, 2020, 10(7): 276.

[7]

NGUYEN P, BADENHORST P E, SHI F, et al. Design of an unmanned ground vehicle and lidar pipeline for the high-throughput phenotyping of biomass in perennial ryegrass [J]. Remote Sensing, 2021, 13(1): 20.

[8]

XU R, LI C. A modular agricultural robotic system(MARS) for precision farming: Concept and implementation [J]. Journal of Field Robotics, 2022, 39(4): 387-409.

[9]

XU R, LI C. A review of high-throughput field phenotyping systems: Focusing on ground robots [J]. Plant Phenomics, 2022.

[10]

CHEN Y, WANG X, ZHANG X, et al. Spectral quantitative analysis and research of fusarium head blight infection degree in wheat canopy visible areas [J]. Agronomy, 2023, 13(3): 933.

[11]

王楠，李震，李佳盟，等．智能型作物植株叶绿素检测系统设计与开发[J/OL]．农业机械学报，1-13[2025-03-01].

WANG Nan, LI Zhen, LI Jiameng, et al. Design and development of intelligent plant chlorophyll index detection system [J]. Transactions of the Chinese Society for Agricultural Machinery, 1-13[2025-03-01].

[12]

XU N, SUN G, BAI Y, et al. Global reconstruction method of maize population at seedling stage based on kinect sensor [J]. Agriculture, 2023, 13(2): 348.

[13]

孙国祥，黄银锋，汪小旵，等．基于LIO-SAM建图和激光视觉融合定位的温室自主行走系统[J]．农业工程学报，2024，40（3）：227-239.

SUN Guoxiang, HUANG Yinfeng, WANG Xiaochan, et al. Autonomous navigation system in a greenhouse using LIO-SAM mapping and laser vision fusion localization [J]. Transactions of the Chinese Society of Agricultural Engineering, 2024, 40(3): 227-239.

[14]

李培艺，汪小旵，王延鑫，等．基于LiDAR多维点云优化的垄作菊花采摘机器人自主导航方法研究[J]．南京农业大学学报，2024，47（04）：809-822.

LI Peiyi, WANG Xiaochan, WANG Yanxin, et al. Autonomous navigation system for chrysanthemum picking robot based on LiDAR multidimensional point cloud optimization [J]. Journal of Nanjing Agricultural University, 2024, 47(4): 809-822.

[15]

孟小前，李俊磊，胡伟，等．基于LiDAR数据与光谱影像融合的单木提取方法[J]．农业机械学报，2024，55（1）：203-211.

MENG Xiaoqian, LI Junlei, HU Wei, et al. Single wood extraction method combining LiDAR data and spectral images [J]. Transactions of the Chinese Society for Agricultural Machinery, 2024, 55(1): 203-211.

[16]

王宇唯，马旭，谭穗妍，等．无人机遥感与地面观测的多模态数据融合反演水稻氮含量[J]．农业工程学报，2024，40（18）：100-109.

WANG Yuwei, MA Xu, TAN Suiyan, et al. Inverting rice nitrogen content with multimodal data fusion of unmanned aerial vehicle remote sensing and ground observations [J]. Transactions of the Chinese Society of Agricultural Engineering, 2024, 40(18): 100-109.

[17]

冯权泷，任燕，姚晓闯，等．基于多源光学雷达数据融合的黄淮海平原冬小麦识别[J]．农业机械学报，2023，54（2）：160-168.

FENG Quanlong, REN Yan, YAO Xiaochuang, et al. Identification of winter wheat in Huang-Huai-Hai Plain based on multi-source optical radar data fusion [J]. Transactions of the Chinese Society for Agricultural Machinery, 2023, 54(2): 160-168.

[18]

QIU Q, FAN Z, MENG Z, et al. Extended ackerman steering principle for the coordinated movement control of a four wheel drive agricultural mobile robot [J]. Computers and Electronics in Agriculture, 2018, 152: 40-50.

[19]

QIU Q, SUN N, BAI H, et al. Field-based high-throughput phenotyping for maize plant using 3D lidar point cloud generated with a “phenomobile” [J]. Frontiers in Plant Science, 2019: 10.

[20]

汪小旵，李泽晟，陈彦宇，等．高地隙农田信息采集机器人设计与试验[J]．农业机械学报，2023，54（6）：65-77.

WANG Xiaochan, LI Zesheng, CHEN Yanyu, et al. Design and experiment of farmland Information collection robot [J]. Transactions of the Chinese Society for Agricultural Machinery, 2023, 54(6): 65-77.

[21]

Technology-Arugga AI Farming [EB/OL]. https://www.arugga.com, 2024-11-24.

[22]

WILLIAMS H, NEJATI M, HUSSEIN S, et al. Autonomous pollination of individual kiwifruit flowers: Toward a robotic kiwifruit pollinator [J]. Journal of Field Robotics, 2020, 37(2): 246-262.

[23]

OHI N, LASSAK K, WATSON R, et al. Design of an autonomous precision pollination robot [C]// 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2018.

[24]

SMITH T, RIJAL M, TATSCH C, et al. Design of stickbug: A six-armed precision pollination robot [J]. 2024.

[25]

LI K, HUO Y, LIU Y, et al. Design of a lightweight robotic arm for kiwifruit pollination [J]. Computers and Electronics in Agriculture, 2022, 198: 107114.

[26]

GAO C, HE L, FANG W, et al. A novel pollination robot for kiwifruit flower based on preferential flowers selection and precisely target [J]. Computers and Electronics in Agriculture, 2023, 207: 107762.

[27]

WEI J, PAN Y, SUN L, et al. A novel redundant cooperative control strategy for robotic pollination [J]. Computers and Electronics in Agriculture, 2024, 220: 108846.

[28]

文朝武，龙洁花，张宇，等．基于3D视觉的番茄授粉花朵定位方法[J]．农业机械学报，2022，53（8）：320-328.

WEN Chaowu, LONG Jiehua, ZHANG Yu, et al. Positioning method of tomato pollination flowers based on 3D vision [J]. Transactions of the Chinese Society for Agricultural Machinery, 2022, 53(8): 320-328.

[29]

赵春江，文朝武，林森，等．基于级联卷积神经网络的番茄花期识别检测方法[J]．农业工程学报，2020，36（24）：143-152.

ZHAO Chunjiang, WEN Chaowu, LIN Sen, et al. Tomato florescence recognition and detection method based on cascaded neural network [J]. Transactions of the Chinese Society of Agricultural Engineering, 2020, 36(24): 143-152.

[30]

MCCOOL C S, BEATTIE J, FIRN J, et al. Efficacy of mechanical weeding tools: A study into alternative weed management strategies enabled by robotics [J]. IEEE Robotics and Automation Letters, 2018: 1184-1190.

[31]

UTSTUMO T, URDAL F, BREVIK A, et al. Robotic in-row weed control in vegetables [J]. Computers and Electronics in Agriculture, 2018, 154: 36-45.

[32]

Autonomous laser weeder demo unit-carbon robotics [EB/OL]. https://carbonrobotics.com/autonomous-weeder, 2024-11-24.

[33]

RAJA R, SU W, SLAUGHTER D C, et al. Real-time precision crop identification in high weed-density environments for robotic weed control using spectral fluorescence imaging in celery [J]. Computers and Electronics in Agriculture, 2025, 231: 110022.

[34]

SULZBACH E, SCHEEREN I, TORRES VERAS M S, et al. Deep learning model optimization methods and performance evaluation of YOLOv8 for enhanced weed detection in soybeans [J]. Computers and Electronics in Agriculture, 2025, 232: 110117.

[35]

李恒达．农田杂草鲜重检测模型与对靶施药系统[D]．哈尔滨：东北农业大学，2022.

LI Hengda. Detection model of farmland weed fresh weight and target application system [D]. Harbin: Northeast Agricultural University, 2022.

[36]

姜伟．面向复杂农田环境的损伤施药行内除草机器人研制[D]．哈尔滨：东北农业大学，2022.

JIANG Wei. Development of an intra-row weeding robot for applying herbicides after injury in complex farmland environment [D]. Harbin: Northeast Agricultural University, 2022.

[37]

OBERTI R, MARCHI M, TIRELLI P, et al. Selective spraying of grapevines for disease control using a modular agricultural robot [J]. Biosystems Engineering, 2016, 146: 203-215.

[38]

CANTELLI L, BONACCORSO F, LONGO D, et al. A small versatile electrical robot for autonomous spraying in agriculture [J]. Agri Engineering, 2019, 1(3): 391-402.

[39]

RINCÓN V J, GRELLA M, MARUCCO P, et al. Spray performance assessment of a remote-controlled vehicle prototype for pesticide application in greenhouse tomato crops [J]. Science of The Total Environment, 2020, 726: 138509.

[40]

江苏岚江智能科技有限公司[EB/OL]．https://www.lanjiangtech.com/，2024-11-24.

[41]

廷捷智蜂—专业果园植保与智慧农业解决方案[EB/OL]．https://smartbee-robot.com，2024-11-24.

[42]

TAN H, ZHAO X, ZHAI C, et al. Design and experiments with a SLAM system for low-density canopy environments in greenhouses based on an improved cartographer framework [J]. Frontiers in Plant Science, 2024, 15.

[43]

张青松，陈志凌，杜文斌，等．遥控自走式雪茄植株中下层烟叶植保喷雾机设计与试验[J]．农业机械学报，2024，55（1）：122-133.

ZHANG Qingsong, CHEN Zhiling, DU Wenbin, et al. Design and experiment of novel sprayer for protecting middle and lower leaves of cigar tobacco plants [J]. Transactions of the Chinese Society for Agricultural Machinery, 2024, 55(1): 122-133.

[44]

BAO X, NIU Y, LI Y, et al. Design and kinematic analysis of cable-driven target spray robot for citrus orchards [J]. Applied Sciences, 2022, 12(18): 9379.

[45]

ZHANG J, YIN H, ZHOU L, et al. Variable rate air-assisted spray based on real-time disease spot identification [J]. Pest Management Science, 2023, 79(1): 402-414.

[46]

极飞科技XAG：提升农业生产效率[EB/OL]．https://www.xa.com/，2024-11-24.

[47]

DJI大疆农业无人机-让农业更轻松，让生命更美好。[EB/OL]．https://ag.dji.com/cn，2024-11-24.

[48]

王志翀，HERBST A，BONDS J，等．植保无人机低空低量施药雾滴沉积飘移分布立体测试方法[J]．农业工程学报，2020，36（4）：54-62.

WANG Zhichong, ANDREAS H, JANE B, et al. Stereoscopic test method for low-altitude and low-volume spraying deposition and drift distribution of plant protection UAV [J]. Transactions of the Chinese Society of Agricultural Engineering, 2020, 36(4): 54-62.

[49]

XU H, YI L, LI C, et al. Design and experiment of ecological plant protection UAV based on ozonated water spraying [J]. Drones, 2023, 7(5): 291.

[50]

沈跃，张凌飞，沈亚运，等．基于相邻争夺算法的无人机多架次植保作业路径规划[J]．农业工程学报，2024，40（16）：44-51.

SHEN Yue, ZHANG Lingfei, SHEN Yayun, et al. Path planning for the multiple drones plant protection operations of UAV based on adjacent contention algorithm [J]. Transactions of the Chinese Society of Agricultural Engineering, 2024, 40(16): 44-51.

[51]

姜锐，周志艳，徐岩，等．植保无人机药箱液量监测装置的设计与试验[J]．农业工程学报，2017，33（12）：107-115.

JIANG Rui, ZHOU Zhiyan, XU Yan, et al. Design and experiment of liquid quantity monitor for pesticide tank in spraying UAV [J]. Transactions of the Chinese Society of Agricultural Engineering, 2017, 33(12): 107-115.

[52]

SILWAL A, YANDUN F, NELLITHIMARU A, et al. Bumblebee: A path towards fully autonomous robotic vine pruning [J]. arXiv e-prints, 2021.

[53]

WILLIAMS H, SMITH D, SHAHABI J, et al. Modelling wine grapevines for autonomous robotic cane pruning [J]. Biosystems Engineering, 2023, 235: 31-49.

[54]

ZAHID A, MAHMUD M S, HE L, et al. Development of an integrated 3R end-effector with a cartesian manipulator for pruning apple trees [J]. Computers and Electronics in Agriculture, 2020, 179: 105837.

[55]

CUEVAS-VELASQUEZ H, GALLEGO A J, TYLECEK R, et al. Real-time stereo visual servoing for rose pruning with robotic arm [J]. Institute of Electrical and Electronics Engineers (IEEE), 2020.

[56]

HUANG C, CAI D, WANG W, et al. Development of an automatic control system for a hydraulic pruning robot [J]. Computers and Electronics in Agriculture, 2023, 214: 108329.

[57]

SONG P, CHEN K, ZHU L, et al. An improved cascade R-CNN and RGB-D camera-based method for dynamic cotton top bud recognition and localization in the field [J]. Computers and Electronics in Agriculture, 2022, 202: 107442.

[58]

马丽娜，徐扬杰，罗承铭，等．茶园自走式修剪机接触式循垄导航系统设计与试验[J]．农业工程学报，2024，40（16）：34-43.

MA Lina, XU Yangjie, LUO Chengming, et al. Design and experiment of the contact-style ridge-following navigation system for a tea garden self-propelled trimming machine [J]. Transactions of the Chinese Society of Agricultural Engineering, 2024, 40(16): 34-43.

[59]

极飞科技XAG：提升农业生产效率[EB/OL]．https://www.xa.com/，2024-11-24.

[60]

纬尔科技：用科技赋能农业生产力[EB/OL]．https://viewer.tech，2024-11-24.

[61]

OCTINION—Engineering the future [EB/OL]. http://www.octinion.com/products, 2024-11-24.

[62]

I'm BERRY, nice to meet you! [EB/OL]. https://www.organifarms.de/product?utm_source=chatgpt.com, 2024-11-24.

[63]

HARVEST CROO ROBOTICS [EB/OL]. https://www.harvestcroorobotics.com/, 2024-11-24.

[64]

Harvesting Robots [EB/OL]. https://dogtooth.tech/products/, 2024-11-24.

[65]

WANG D, WANG X, CHEN Y, et al. Strawberry ripeness classification method in facility environment based on red color ratio of fruit rind [J]. Computers and Electronics in Agriculture, 2023, 214: 108313.

[66]

刘莫尘，褚镇源，崔明诗，等．基于改进YOLO v8-Pose的红熟期草莓识别和果柄检测[J]．农业机械学报，2023，54（S2）：244-251.

LIU Mochen, CHU Zhenyuan, CUI Mingshi, et al. Red ripe strawberry recognition and stem detection based on improved YOLO v8-Pose [J]. Transactions of the Chinese Society for Agricultural Machinery, 2023, 54 (S2): 244-251.

[67]

杨珍，龚惟新，李凯，等．高架草莓的果实识别与果梗分割[J]．农业工程学报，2023，39（17）：172-181.

YANG Zhen, GONG Weixin, LI Kai, et al. Fruit recognition and stem segmentation of the elevated planting of strawberries [J]. Transactions of the Chinese Society of Agricultural Engineering, 2023, 39(17): 172-181.

[68]

FENG Q, CHEN J, ZHANG M, et al. Design and test of harvesting robot for table-top cultivated strawberry [C]//IEEE, 2019.

[69]

ZHANG Y, ZHANG K, YANG L, et al. Design and simulation experiment of ridge planting strawberry picking manipulator [J]. Computers and Electronics in Agriculture, 2023, 208: 107690.

[70]

DU X, CHENG H, MA Z, et al. DSW-YOLO: A detection method for ground-planted strawberry fruits under different occlusion levels [J]. Computers and Electronics in Agriculture, 2023, 214: 108304.

[71]

WANG F, URQUIZO R C, ROBERTS P, et al. Biologically inspired robotic perception-action for soft fruit harvesting in vertical growing environments [J]. Precision Agriculture, 2023, 24(3): 1072-1096.

[72]

XIONG Y, GE Y, FROM P J. An improved obstacle separation method using deep learning for object detection and tracking in a hybrid visual control loop for fruit picking in clusters [J]. Computers and Electronics in Agriculture, 2021, 191: 106508.

[73]

杨震宇，汪小旵，祁子涵，等．基于改进YOLOv8的草莓识别与果梗采摘关键点检测[J]．农业工程学报，2024，40（18）：167-175.

YANG Zhenyu, WANG Xiaochan, QI Zihan, et al. Recognizing strawberry to detect key points for peduncle picking using improved YOLOv8 model [J]. Transactions of the Chinese Society of Agricultural Engineering, 2024, 40(18): 167-175.

[74]

FFRobotics [EB/OL]. https://www.ffrobotics.com/, 2024-11-24.

[75]

RIPE ROBOTICS [EB/OL]. https://www.riperobotics.com/#mission, 2024-11-24.

[76]

SILWAL A, DAVIDSON J R, KARKEE M, et al. Design, integration, and field evaluation of a robotic apple harvester [J]. Journal of Field Robotics, 2017, 34(6): 1140-1159.

[77]

ZHU F, ZHANG W, WANG S, et al. Apple-harvesting robot based on the YOLOv5-RACF model [J]. Biomimetics, 2024, 9(8): 495.

[78]

赵德安，吴任迪，刘晓洋，等．气电混合驱动全天候苹果收获机器人设计与试验[J]．农业机械学报，2020，51（2）：21-28，36.

ZHAO Dean, WU Rendi, LIU Xiaoyang, et al. Design and experiment of apple harvesting robot based on gas-electric hybrid drive [J]. Transactions of the Chinese Society for Agricultural Machinery, 2020, 51(2): 21-28, 36.

[79]

HU G, CHEN C, CHEN J, et al. Simplified 4-DOF manipulator for rapid robotic apple harvesting [J]. Computers and Electronics in Agriculture, 2022, 199.

[80]

冯青春，赵春江，李涛，等．苹果四臂采摘机器人系统设计与试验[J]．农业工程学报，2023，39（13）：25-33.

FENG Qingchun, ZHAO Chunjiang, LI Tao, et al. Design and test of a four-arm apple harvesting robot [J]. Transactions of the Chinese Society of Agricultural Engineering, 2023, 39(13): 25-33.

[81]

史帅旗，杨福增，刘志杰，等．复合气动式苹果采摘手设计与试验[J]．农业机械学报，2024，55（10）：93-105.

SHI Shuaiqi, YANG Fuzeng, LIU Zhijie, et al. Design and experiment of composite pneumatic apple picking manipulator [J]. Transactions of the Chinese Society for Agricultural Machinery, 2024, 55(10): 93-105.

[82]

江自真，周俊，韩宏琪，等．基于RANSAC拟合点云去噪的苹果采摘位姿构建方法[J]．农业机械学报，2024，55（10）：72-81.

JIANG Zizhen, ZHOU Jun, HAN Hongqi, et al. Apple picking pose establishment based on filtering point-cloud noise by RANSAC fitting [J]. Transactions of the Chinese Society for Agricultural Machinery, 2024, 55 (10): 72-81.

[83]

Nanovel [EB/OL]. https://www.nanovel.ag/technology, 2024-11-24.

[84]

刘静，林冲，郭世财，等．柑橘类水果采摘机器的设计与研究[J]．包装工程，2019，40（17）：56-62.

LIU Jing, LIN Chong, GUO Shicai, et al. Design and research of citrus fruit picking machine [J]. Packaging Engineering, 2019, 40(17): 56-62.

[85]

TANG Z, XU L, WANG Y, et al. Collision-free motion planning of a six-link manipulator used in a citrus picking robot [J]. Applied Sciences, 2021, 11(23): 11336.

[86]

YIN H, SUN Q, REN X, et al. Development, integration, and field evaluation of an autonomous citrus-harvesting robot [J]. Journal of Field Robotics, 2023, 40(6): 1363-1387.

[87]

鲍秀兰，马志涛，马萧杰，等．丘陵果园自然环境下柑橘采摘机器人设计与试验[J]．农业机械学报，2024，55（4）：124-135.

BAO Xiulan, MA Zhitao, MA Xiaojie, et al. Design and experiment of citrus picking robot in hilly orchard natural environment [J]. Transactions of the Chinese Society for Agricultural Machinery, 2024, 55(4): 124-135.

[88]

王毅，许洪斌，张茂，等．仿蛇嘴咬合式柑橘采摘末端执行器设计与实验[J]．农业机械学报，2018，49（10）：54-64.

WANG Yi, XU Hongbin, ZHANG Mao, et al. Design and experiment of bite-model end-effector for citrus harvesting by simulating with mouth of snake [J]. Transactions of the Chinese Society for Agricultural Machinery, 2018, 49(10): 54-64.

[89]

XIAO X, WANG Y, ZHOU B, et al. Flexible hand claw picking method for citrus-picking robot based on target fruit recognition [J]. Agriculture, 2024, 14(8): 1227.

[90]

WILLIAMS H A M, JONES M H, NEJATI M, et al. Robotic kiwifruit harvesting using machine vision, convolutional neural networks, and robotic arms [J]. Biosystems Engineering, 2019, 181: 140-156.

[91]

MA L, HE Z, ZHU Y, et al. A method of grasping detection for kiwifruit harvesting robot based on deep learning [J]. Agronomy, 2022, 12(12): 3096.

[92]

WANG Y, HE Z, CAO D, et al. Coverage path planning for kiwifruit picking robots based on deep reinforcement learning [J]. Computers and Electronics in Agriculture, 2023, 205: 107593.

[93]

王佳虹，王迪，叶宏宝，等．猕猴桃采摘机器人设计及试验[J]．浙江农业科学，2023，64（10）：2418-2422.

WANG Jiahong, WANG Di, YE Hongbao, et al. Design and experiment of kiwi fruit picking robot [J]. Journal of Zhejiang Agricultural Sciences, 2023, 64(10): 2418-2422.

[94]

XIONG J, HE Z, LIN R, et al. Visual positioning technology of picking robots for dynamic litchi clusters with disturbance [J]. Computers and Electronics in Agriculture, 2018, 151: 226-237.

[95]

LI J, TANG Y, ZOU X, et al. Detection of fruit-bearing branches and localization of litchi clusters for vision-based harvesting robots [J]. IEEE Access, 2020, 8: 117746-117758.

[96]

WANG C, LI C, HAN Q, et al. A performance analysis of a litchi picking robot system for actively removing obstructions, using an artificial intelligence algorithm [J]. Agronomy, 2023, 13(11): 2795.

[97]

LING X, ZHAO Y, GONG L, et al. Dual-arm cooperation and implementing for robotic harvesting tomato using binocular vision [J]. Robotics and Autonomous Systems, 2019, 114: 134-143.

[98]

于丰华，周传琦，杨鑫，等．日光温室番茄采摘机器人设计与试验[J]．农业机械学报，2022，53（1）：41-49.

YU Fenghua, ZHOU Chuanqi, YANG Xin, et al. Design and experiment of tomato picking robot in solar greenhouse [J]. Transactions of the Chinese Society for Agricultural Machinery, 2022, 53(1): 41-49.

[99]

LI Y, FENG Q, ZHANG Y, et al. Peduncle collision-free grasping based on deep reinforcement learning for tomato harvesting robot [J]. Computers and Electronics in Agriculture, 2024, 216: 108488.

[100]

GONG L, WANG W, WANG T, et al. Robotic harvesting of the occluded fruits with a precise shape and position reconstruction approach [J]. Journal of Field Robotics, 2022, 39(1): 69-84.

[101]

WANG L L, ZHAO B, FAN J W, et al. Development of a tomato harvesting robot used in greenhouse [J]. International Journal of Agricultural and Biological Engineering, 2017, 10(4): 140-149.

[102]

PARK Y, SEOL J, PAK J, et al. Human-centered approach for an efficient cucumber harvesting robot system: Harvest ordering, visual servoing, and end-effector [J]. Computers and Electronics in Agriculture, 2023, 212: 108116.

[103]

张帆，张帅辉，张俊雄，等．温室黄瓜采摘机器人系统设计[J]．农业工程技术，2020，40（25）：16-20.

ZHANG Fan, ZHANG Shuaihui, ZHANG Junxiong, et al. Design of greenhouse cucumber picking robot system [J]. Applied Engineering Technology, 2020, 40 (25): 16-20.

[104]

AVL Motion [EB/OL]. https://www.avlmotion.com/nl/?utm_source=chatgpt.com, 2024-11-24.

[105]

LEU A, RAZAVI M, LANGSTADTLER L, et al. Robotic Green Asparagus Selective Harvesting [J]. IEEE/ASME Transactions on Mechatronics, 2017, 22(6): 2401-2410.

[106]

LAJPAH S, MUNIH M, MIHELJ M. Mobile robot system for selective asparagus harvesting [J]. Agronomy, 2023, 13(7): 1766.

[107]

汪小旵，李为民，王琳，等．基于改进YOLACT++的成熟芦笋检测-判别-定位方法[J]．农业机械学报，2023，54（7）：259-271.

WANG Xiaochan, LI Weimin, WANG Lin, et al. Method of detection-discrimination-localization for mature asparagus based on improved YOLACT++ algorithm [J]. Transactions of the Chinese Society for Agricultural Machinery, 2023, 54(7): 259-271.

[108]

刘雪美，杜帅，苑进，等．白芦笋选择性收获机末端执行器作业分析与试验[J]．农业机械学报，2018，49（4）：110-120.

LIU Xuemei, DU Shuai, YUAN Jin, et al. Analysis and experiment on selective harvesting mechanical end-effector of white asparagus [J]. Transactions of the Chinese Society for Agricultural Machinery, 2018, 49 (4): 110-120.

[109]

ZHANG P, DAI N, LIU X, et al. A novel lightweight model HGCA-YOLO: Application to recognition of invisible spears for white asparagus robotic harvesting [J]. Computers and Electronics in Agriculture, 2024, 220: 108852.

[110]

BAC C W, HEMMING J, TUIJL B A J, et al. Performance evaluation of a harvesting robot for sweet pepper [J]. Journal of Field Robotics, 2017, 34(6): 1123-1139.

[111]

LEHNERT C, ENGLISH A, MCCOOL C, et al. Autonomous sweet pepper harvesting for protected cropping systems [J]. IEEE Robotics and Automation Letters, 2017, 2(2): 872-879.

[112]

RINGDAHL O, KURTSER P, EDAN Y. Evaluation of approach strategies for harvesting robots: Case study of sweet pepper harvesting [J]. Journal of Intelligent &Robotic Systems, 2019, 95(1): 149-164.

[113]

ARAD B, BALENDONCK J, BARTH R, et al. Development of a sweet pepper harvesting robot [J]. Journal of Field Robotics, 2020, 37(6): 1027-1039.

[114]

POLIC M, TABAK J, ORSAG M. Pepper to fall: A perception method for sweet pepper robotic harvesting [J]. Intelligent Service Robotics, 2022, 15(2): 193-201.

[115]

汪龙．基于卷积神经网络的语义分割算法研究及其在甜椒图像识别中的应用[D]．镇江：江苏大学，2021.

WANG Long. Research of semantic segmentation algorithm based on convolution neural network and its application in image recognition of sweet pepper [D]. Zhenjiang: Jiangsu University, 2021.

[116]

MAVRIDIS P, MAVRIKIS N, MASTROGEORGIOU A, et al. Low-cost, accurate robotic harvesting system for existing mushroom farms [C]. IEEE, 2023.

[117]

RONG J, WANG P, YANG Q, et al. A field-tested harvesting robot for oyster mushroom in greenhouse [J]. Agronomy, 2021, 11(6): 1210.

[118]

施浩楠．移动式仿人双孢菇采摘机器人设计[D]．南京：南京农业大学，2021.

SHI Haonan. Design of mobile robot for picking bisporus mushroom [D]. Nanjing: Nanjing Agricultural University, 2021.

[119]

周顺．面向工厂化生产的瓶栽白玉菇采收装置设计与试验[D]．泰安：山东农业大学，2023.

ZHOU Shun. Design and test of the bottle-planted white hypsizygus marmoreus harvesting device for factory production [D]. Tai'an: Shandong Agricultural University, 2023.

[120]

ZHAO K, LI H, JI J, et al. Pressure-stabilized flexible end-effector for selective picking of agaricus bisporus [J]. Agriculture, 2023, 13(12): 2256.

[121]

孙龙霞，吕宁，於锋，等．蘑菇采摘机器人的结构设计及优化[J]．江苏大学学报（自然科学版），2024，45（3）：295-301.

SUN Longxia, LÜ Ning, YU Feng, et al. Structure design and optimization of mushroom picking robot [J]. Journal of Jiangsu University(Natural Science Edition), 2024, 45(3): 295-301.

[122]

Vision+Robotics [EB/OL]. https://www.wur.nl/en/research-results/research-institutes/plant-research/vision-robotics-3.htm, 2024-11-24.

[123]

新疆莎车县：“机器人”进田地解农户“采摘之忧”[EB/OL]．https://www.robot-china.com/news/202309/04/84624.html，2024-11-24.

[124]

科技把控未来犍小茉第三代茉莉花采摘机器人荣耀面市[EB/OL]．https://www.jxsg-tech.com/newsinfo/1100157.html，2024-11-24.

[125]

陈飞，葛云，张立新，等．红花采摘机器人集条预定位机构设计与试验[J]．农业工程学报，2021，37（15）：10-19.

CHEN Fei, GE Yun, ZHANG Lixin, et al. Design and experiment of the strip-collected pre-positioning mechanism for safflower picking robots [J]. Transactions of the Chinese Society of Agricultural Engineering, 2021, 37(15): 10-19.

[126]

郭辉，陈海洋，高国民，等．基于YOLOv5m的红花花冠目标检测与空间定位方法[J]．农业机械学报，2023，54（7）：272-281.

GUO Hui, CHEN Haiyang, GAO Guomin, et al. Safflower corolla object detection and spatial positioning methods based on YOLOv5m [J]. Transactions of the Chinese Society for Agricultural Machinery, 2023, 54(7): 272-281.

[127]

王延鑫，汪小旵，李培艺，等．包络式金丝皇菊采摘机械手设计与试验优化[J]．南京农业大学学报，1-18[2025-03-03].

WANG Yanxin, WANG Xiaochan, LI Peiyi, et al. Design and experimental optimization of an enveloping golden chrysanthemum harvesting manipulator [J]. Journal of Nanjing Agricultural University, 1-18[2025-03-03].

[128]

陶澄宇．自主采茶机器人的茶叶剪切位置视觉识别及导引研究[D]．上海：上海交通大学，2021.

TAO Chengyu. Visual recognition and guidance of tea cutting position for autonomous tea picking robot [D]. Shanghai: Shanghai Jiao Tong University, 2021.

[129]

XU L, XIE Y, CHEN X, et al. Design of an efficient combined multipoint picking scheme for tea buds [J]. Frontiers in Plant Science, 2022, 13.

[130]

李亚涛．茶叶采摘机器人的视觉检测与定位技术研究[D]．杭州：浙江理工大学，2022.

LI Yatao. Research on the visual detection and localization technology of tea harvesting robot [D]. Hangzhou: Zhejiang Sci-Tech University, 2022.

[131]

蒋宗祥．多臂协同的名优茶单芽精准采摘机器人研究[D]．泰安：山东农业大学，2022.

JIANG Zongxiang. Research on the precise picking robot of high-quality tea sprout with multi-arm coordination [D]. Tai'an: Shandong Agricultural University, 2022.

[132]

LIN G, XIONG J, ZHAO R, et al. Efficient detection and picking sequence planning of tea buds in a high-density canopy [J]. Computers and Electronics in Agriculture, 2023, 213: 108213.

[133]

WU Y, CHEN J, WU S, et al. An improved YOLOv7 network using RGB-D multi-modal feature fusion for tea shoots detection [J]. Computers and Electronics in Agriculture, 2024, 216: 108541.

[134]

WU L, LIU H, YE C, et al. Development of a premium tea-picking robot incorporating deep learning and computer vision for leaf detection [J]. Applied Sciences, 2024, 14(13): 5748.

[135]

陈建能，陈倩雯，刘林敏，等．旋转式两工位名优茶采摘收集一体末端执行器设计与试验[J]．农业机械学报，2024，55（10）：136-144.

CHEN Jianneng, CHEN Qianwen, LIU Linmin, et al. Design and experiment of rotating two workstations integrated effector for famous tea picking and collection [J]. Transactions of the Chinese Society for Agricultural Machinery, 2024, 55(10): 136-144.

[136]

蔡其锴．名优茶采摘机器人的视觉识别和采摘技术研究[D]．成都：电子科技大学，2024.

CAI Qikai. Research on visual recognition and picking technology of tea picking robot [D]. Chengdu: University of Electronic Science and Technology of China, 2024.

[137]

白振伟，严富威，袁培海，等．基于嵌入式机器视觉智能果实分拣机器人设计与试验[J]．智能化农业装备学报（中英文），2023，4（3）：61-70.

BAI Zhenwei, YAN Fuwei, YUAN Peihai, et al. Design and experiment of fruit sortingrobot based on embedded machine vision [J]. Journal of Intelligent Agricultural Mechanization, 2023, 4(3): 61−70.

2025年第6卷第2期

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doi: 10.12398/j.issn.2096-7217.2025.02.001

接收时间：2025-03-04
首发时间：2026-11-05
出版时间：2025-05-15

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出版历史

收稿日期：2025-03-04
修回日期：2025-04-02

基金

National Key Research and Development Program of China(2023YFD2000304)

国家重点研发计划项目(2023YFD2000304)

Jiangsu Provincial Key Research and Development Program(BE2021302)

江苏省重点研发计划项目(BE2021302)

Jiangsu Agricultural Science and Technology Innovation Fund Program(CX（21）2006)

江苏省农业科技自主创新资金项目(CX（21）2006)

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南京农业大学工学院，江苏南京，210031

通讯作者:

^* 汪小旵，男，1968年生，安徽安庆人，博士，教授；研究方向为农业机器人、农业装备电动化智能化控制。E-mail：wangxiaochan@njau.edu.cn

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2种不同金属材料的力学参数

科 Family	属数 Number of genus	种数 Number of species	占总种数比例 Percentage of total species (%)	属 Genus	种数 Number of species	占总种数比例 Percentage of total species (%)
鹅膏菌科Amanitaceae	2	11	5.26	鹅膏菌属 Amanita	10	4.78
小菇科 Mycenaceae	2	12	5.74	丝盖伞属 Inocybe	5	2.39
多孔菌科 Polyporaceae	8	14	6.70	蜡蘑属 Laccaria	5	2.39
红菇科 Russulaceae	3	23	11.00	小皮伞属 Marasmius	6	2.87
				小菇属 Mycena	11	5.26
				光柄菇属 Pluteus	5	2.39
				红菇属 Russula	17	8.13
				栓菌属 Trametes	5	2.39

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