智能化农业装备学报（中英文）

人工智能在畜禽养殖机器人中的应用与展望

预览PDF | 下载PDF

王克林 ¹^,² , 刘龙申 ²^,³ , 陈金鑫 ¹^,² , 李鹏 ²^,³ , Cedric OKINDA ¹^,²^,⁴ , 沈明霞 ²^,³^,^*^,^*

智能化农业装备学报（中英文） | 2025,6(2): 44-57

收起

智能化农业装备学报（中英文） | 2025 , 6 (2) : 44 -57

人工智能在畜禽养殖机器人中的应用与展望

全屏

王克林¹^,², 刘龙申²^,³, 陈金鑫¹^,², 李鹏²^,³, Cedric OKINDA¹^,²^,⁴, 沈明霞²^,³^,^*^,^*

作者信息

^1.南京农业大学工学院，江苏南京，210031

^2.农业农村部养殖装备重点实验室，江苏南京，210031

^3.南京农业大学人工智能学院，江苏南京，210031

^4.马辛德穆利罗科技大学，肯尼亚卡卡梅加，190-50100

通讯作者:

^* 沈明霞，女，1964年生，江苏常熟人，博士，教授，博导；研究方向为机器视觉与信息农业。E-mail：mingxia@njau.edu.cn

作者简介:

王克林，男，1998年生，江苏徐州人，博士研究生；研究方向为机器视觉和信息农业。E-mail：2024212017@stu.njau.edu.cn

Application and prospect of artificial intelligence in livestock and poultry farming robots

Kelin WANG¹^,², Longshen LIU²^,³, Jinxin CHEN¹^,², Peng LI²^,³, Cedric OKINDA¹^,²^,⁴, Mingxia SHEN²^,³

Affiliations

^1.College of Engineering, Nanjing Agricultural University, Nanjing 210031, China

^2.Key Laboratory of Farming Equipment, Ministry of Agriculture and Rural Affairs, Nanjing 210031, China

^3.College of Artificial Intelligence, Nanjing Agricultural University, Nanjing 210031, China

^4.Masinde Muliro University of Science and Technology, Kakamega 190-50100, Kenya

Corresponding Author:

^* SHEN Mingxia, E-mail: mingxia@njau.edu.cn

WANG Kelin, E-mail: 2024212017@stu.njau.edu.cn

出版时间: 2025-05-15 doi: 10.12398/j.issn.2096-7217.2025.02.004

文章导航

摘要

收起

我国畜禽养殖量常年居于世界前列，不仅养殖种类齐全，且产业链与相关配套完整，在农业产业中占有举足轻重的地位。近年来，由于规模化养殖的快速发展以及动物疫病流行、劳动力短缺等因素，养殖产业对智能化、无人化的养殖设备提出了更高的需求。其中，养殖机器人作为实现智慧化养殖的重要载体，可有效替代或协助人类完成部分工作，且对于提升动物福利、提高生产效率、减少污染浪费等方面具有重大意义和广阔前景。本研究综述了图像识别、深度学习、强化学习、自主导航等智能技术及热红外相机、深度相机、激光雷达等关键零部件在养殖机器人上的应用，并介绍了其可实现的例如动物生理信息检测、行为姿态识别、环境监测调控、饲料蛋奶管理等多种功能。此外，由于我国自动化养殖产业起步较晚，目前与发达国家仍存在一定差距，因此，本研究亦针对目前国内外智能化养殖机器人的产业现状和方向进行了介绍，并探讨了其背后发展历程、市场前景和政策支撑。本研究还展望了未来智能养殖行业的发展，指出了当前技术在经济性、稳定性、动物接受度等方面存在的挑战，并提出了未来可能的前进方向和改进目标，旨在为相关研究人员进一步推动技术革新和产业应用提供参考。

关键词

人工智能 / 农业机器人 / 智慧养殖 / 深度学习 / 畜禽养殖

Abstract

收起

Chinese livestock and poultry farming sector consistently ranks among the global leaders in production volume. It not only has a comprehensive range of farming types, but also has a complete industrial chain with associated supporting infrastructure, and occupies a pivotal position in the agricultural industry. In recent years, due to the rapid development of large-scale farming, increased prevalence of animal diseases, persistent labor shortages and other factor shave intensified the demands for intelligent and automated farming equipment. Farming robots, as an important carrier for realizing intelligent agriculture, can effectively replace or assist humans in various tasks, and have great significance and broad prospects for enhancing animal welfare, improving production efficiency, and reducing pollution and waste. This article reviews the application of intelligent technologies such as image recognition, deep learning, reinforcement learning, and autonomous navigation, as well as key components such as thermal infrared cameras, depth cameras, and LiDAR in farming robots, and introduces its achievable functions such as animal physiological information detection, behavior posture recognition, environmental monitoring and control, and feed and milk management. In addition, considering that China’s automated commenced development more recently, there is still a developmental gap compared to some developed countries. Therefore, this article examines the current industrial status and direction of intelligent farming robots both domestically (in China) and internationally, which includes an exploration of its development history, market prospects and policy support. This article also looks forward to the future development of the smart farming industry, points out the challenges of current technologies in terms of economy, stability, animal acceptance, etc., and proposes possible future directions and improvement goals, aiming to provide a reference for relevant researchers to further promote technological innovation and industrial applications.

Key words

artificial intelligence / agricultural robots / smart farming / deep learning / livestock and poultry farming

引用本文

王克林, 刘龙申, 陈金鑫, 李鹏, Cedric OKINDA, 沈明霞. 人工智能在畜禽养殖机器人中的应用与展望. 智能化农业装备学报（中英文）, 2025 , 6 (2) : 44 -57 . DOI: 10.12398/j.issn.2096-7217.2025.02.004

Kelin WANG, Longshen LIU, Jinxin CHEN, Peng LI, Cedric OKINDA, Mingxia SHEN. Application and prospect of artificial intelligence in livestock and poultry farming robots[J]. Journal of Intelligent Agricultural Mechanization, 2025 , 6 (2) : 44 -57 . DOI: 10.12398/j.issn.2096-7217.2025.02.004

基金

收起

国家重点研发计划(2021YFD2000800)

参考文献

收起

文献

收起

参考文献引证文献

排序方式：

[1]

中华人民共和国农业农村部．农村农业部生猪专题[EB/OL]．（2023-12-31）[2024-07-10]．http://www.moa.gov.cn/ztzl/szcpxx/.

[2]

中国国家统计局．中华人民共和国2023年国民经济和社会发展统计公报[EB/OL]．（2024-02-29）[2024-07-10]．https://www.stats.gov.cn/sj/zxfb/202402/t20240228_1947915.html.

[3]

前瞻产业研究院．2023年中国生猪养殖行业市场规模、竞争格局及发展前景[EB/OL]．（2023-01-15）[2024-07-10]．https://bg.qianzhan.com/trends/detail/506/230202-f2d95fd4.html.

[4]

沈明霞，陈金鑫，丁奇安，等．生猪自动化养殖装备与技术研究进展与展望[J]．农业机械学报，2022，53（12）：1-19.

SHEN Mingxia, CHEN Jinxin, DING Qi'an, et al. Current situation and development trend of pig automated farming equipment application [J]. Transactions of the Chinese Society for Agricultural Machinery, 2022, 53(12): 1-19.

[5]

中华人民共和国农业农村部．农业农村部关于加快畜牧业机械化发展的意见[EB/OL]．（2020-02-17）[2024-07-10]．http://www.njhs.moa.gov.cn/tzggjzcjd/202002/t20200217_6337230.htm.

[6]

中华人民共和国农业农村部．“十四五”全国畜牧兽医行业发展规划[EB/OL]．（2021-12-14）[2024-07-11]．https://www.gov.cn/zhengce/zhengceku/2021-12/22/5663947/files/fd62c2ed4d3d450e8b0f87c2dc8ff326.pdf.

[7]

王儒敬，孙丙宇．农业机器人的发展现状及展望[J]．中国科学院院刊，2015，30（6）：803-809.

WANG Rujing, SUN Bingyu. Current status and prospects of agricultural robots [J]. Bulletin of the Chinese Academy of Sciences, 2015, 30(6): 803-809.

[8]

胡惠玥，杨小玲，刘仁鑫，等．畜禽养殖机器人研究现状与展望[J]．南方农机，2023，54（19）：1-6，10.

HU Huiyue, YANG Xiaoling, LIU Renxin, et al. Research status and prospects of livestock and poultry breeding robots [J]. Southern Agricultural Machinery, 2023, 54(19): 1-6, 10.

[9]

ROWE E, DAWKINS M S, GEBHARDT-HENRICH S G. A systematic review of precision livestock farming in the poultry sector: Is technology focussed on improving bird welfare [J]. Animals, 2019, 9(9): 614.

[10]

唐瑜嵘，沈明霞，薛鸿翔，等．人工智能技术在畜禽养殖业的发展现状与展望[J]．智能化农业装备学报（中英文），2023，4（1）：1-16.

TANG Yurong, SHEN Mingxia, XUE Hongxiang, et al. Development status and prospect of artificial intelligence technology in livestock and poultry breeding [J]. Journal of Intelligent Agricultural Mechanization, 2023, 4 (1): 1-16.

[11]

BANHAZI T M, BLACK J L. Precision livestock farming: A suite of electronic systems to ensure the application of best practice management on livestock farms [J]. Australian Journal of Multi-disciplinary Engineering, 2009, 7(1): 1-14.

[12]

GEFFEN O, YITZHAKY Y, BARCHILON N, et al. A machine vision system to detect and count laying hens in battery cages [J]. Animal, 2020, 14(12): 2628-2634.

[13]

张岩琪，周硕，张凝，等．基于改进实例分割算法的区域养殖生猪计数系统[J]．智慧农业（中英文），2024，6（4）：53-63.

ZHANG Yanqi, ZHOU Shuo, ZHANG Ning, et al. Regional pig counting system based on improved instance segmentation algorithm [J]. Smart Agriculture, 2024, 6(4): 53-63.

[14]

XIAO J, LIU G, WANG K, et al. Cow identification in free-stall barns based on an improved Mask R-CNN and an SVM [J]. Computers and Electronics in Agriculture, 2022, 194: 106738.

[15]

丁奇安，刘龙申，陈佳，等．基于Jetson Nano+YOLO v5的哺乳期仔猪目标检测[J]．农业机械学报，2022，53（3）：277-284.

DING Qi'an, LIU Longshen, CHEN Jia, et al. Target detection of suckling piglets based on Jetson Nano+YOLO v5 [J]. Transactions of the Chinese Society for Agricultural Machinery, 2022, 53(3): 277-284.

[16]

张燕飞．两轮自主控制鸡舍巡检机器人路径规划研究[D]．太原：中北大学，2023.

ZHANG Yanfei. Research on path planning of two-wheeled autonomous control chicken house inspection robot [D]. Taiyuan: North University of China, 2023.

[17]

沈明霞，太猛，CEDRIC Okinda，等．基于深层卷积神经网络的初生仔猪目标实时检测方法[J]．农业机械学报，2019，50（8）：270-279.

SHEN Mingxia, TAI Meng, CEDRIC Okinda, et al. Real-time detection method for newborn piglets based on deep convolutional neural network [J]. Transactions of the Chinese Society for Agricultural Machinery, 2019, 50(8): 270-279.

[18]

MASELYNE J, ADRIAENS I, HUYBRECHTS T, et al. Measuring the drinking behaviour of individual pigs housed in group using radio frequency identification(RFID) [J]. Animal, 2016, 10(9): 1557-1566.

[19]

杨断利，王永胜，陈辉，等．基于SEEC-YOLO v5s的散养蛋鸡日常行为识别与统计系统[J]．农业机械学报，2023，54（9）：316-328.

YANG Duanli, WANG Yongsheng, CHEN Hui, et al. Daily behavior recognition and statistical system of free-range laying hens based on SEEC-YOLO v5s [J]. Transactions of the Chinese Society for Agricultural Machinery, 2023, 54(9): 316-328.

[20]

刘龙申，舒翠霓，李波，等．基于EfficientDet的围产期母猪姿态识别[J]．农业机械学报，2022，53（4）：271-279.

LIU Longshen, SHU Cuini, LI Bo, et al. Posture recognition of peripartum sows based on EfficientDet [J]. Transactions of the Chinese Society for Agricultural Machinery, 2022, 53(4): 271-279.

[21]

马肄恒．面向笼养肉鸭行为与死亡识别的自主巡检装备创制[D]．杭州：浙江科技大学，2024.

MA Yiheng. Creation of autonomous inspection equipment for behavior and death identification of caged ducks [D]. Hangzhou: Zhejiang University of Science and Technology, 2024.

[22]

陆舟，沈明霞，刘龙申，等．基于轻量化网络与注意力机制的育肥猪采食行为识别方法研究[J]．南京农业大学学报，2023，46（4）：802-812.

LU Zhou, SHEN Mingxia, LIU Longshen, et al. Research on the recognition method of fattening pig feeding behavior based on lightweight network and attention mechanism [J]. Journal of Nanjing Agricultural University, 2023, 46(4): 802-812.

[23]

LI G, JV Q, LIU F, et al. Pig pose recognition method based on openpose [C]// Advances in Precision Instruments and Optical Engineering: Proceedings of the International Conference on Precision Instruments and Optical Engineering, 2021. Singapore: Springer Nature Singapore, 2022: 533-545.

[24]

田浩楠，华婧伊，张少帅，等．基于红外热成像与线性回归拟合的母猪体温检测技术研究[J]．智能化农业装备学报（中英文），2023，4（1）：36-41.

[25]

谢秋菊，刘学飞，郑萍，等．畜禽体温自动监测技术及应用研究进展[J]．农业工程学报，2022，38（15）：212-225.

XIE Qiuju, LIU Xuefei, ZHENG Ping, et al. Research progress on automatic monitoring technology and application of livestock and poultry body temperature [J]. Transactions of the Chinese Society of Agricultural Engineering, 2022, 38(15): 212-225.

[26]

DOESCHL A B, WHITTEMORE C T, KNAP P W, et al. Using visual image analysis to describe pig growth in terms of size and shape [J]. Animal Science, 2004, 79(4): 415-427.

[27]

KIM N Y, KIM S J, OH M, et al. Changes in facial surface temperature of laying hens under different thermal conditions [J]. Animal Bioscience, 2020, 34 (7): 1235-1242.

[28]

周艳青，薛河儒，白洁，等．基于图像的羊体尺参数测点检测方法的研究[J]．内蒙古农业大学学报（自然科学版），2024，45（2）：69-77.

ZHOU Yanqing, XUE Heru, BAI Jie, et al. Research on the detection method of sheep body size parameters based on image [J]. Journal of Inner Mongolia Agricultural University (Natural Science Edition), 2024, 45(2): 69-77.

[29]

MORTENSEN A K, LISOUSKI P, AHRENDT P. Weight prediction of broiler chickens using 3D computer vision [J]. Computers and Electronics in Agriculture, 2016, 123: 319-326.

[30]

肖德琴，林思聪，刘勤，等．基于红外热成像的生猪耳温自动提取算法[J]．农业机械学报，2021，52（8）：255-262.

XIAO Deqin, LIN Sicong, LIU Qin, et al. Automatic extraction algorithm of pig ear temperature based on infrared thermal imaging [J]. Transactions of the Chinese Society for Agricultural Machinery, 2021, 52 (8): 255-262.

[31]

XIONG X, LU M, YANG W, et al. An automatic head surface temperature extraction method for top-view thermal image with individual broiler [J]. Sensors, 2019, 19(23): 5286.

[32]

WANG Y, KANG X, CHU M, et al. Deep learning-based automatic dairy cow ocular surface temperature detection from thermal images [J]. Computers and Electronics in Agriculture, 2022, 202: 107429.

[33]

CHEN H, LIANG Y, HUANG H, et al. Live pig-weight learning and prediction method based on a multilayer RBF network [J]. Agriculture, 2023, 13(2): 253.

[34]

GJERGJI M, DE MORAES WEBER V, SILVA L O C, et al. Deep learning techniques for beef cattle body weight prediction [C]// 2020 International Joint Conference on Neural Networks (IJCNN). IEEE, 2020: 1-8.

[35]

XUE H, SHEN M, SUN Y, et al. Instance segmentation and ensemble learning for automatic temperature detection in multiparous sows [J]. Sensors, 2023, 23(22): 9128.

[36]

ZHANG B, XIAO D, LIU J, et al. Pig eye area temperature extraction algorithm based on registered images [J]. Computers and Electronics in Agriculture, 2024, 217: 108549.

[37]

李卓，毛涛涛，刘同海，等．基于机器视觉的猪体质量估测模型比较与优化[J]．农业工程学报，2015，31（2）：155-161.

LI Zhuo, MAO Taotao, LIU Tonghai, et al. Comparison and optimization of pig body mass estimation models based on machine vision [J]. Transactions of the Chinese Society of Agricultural Engineering, 2015, 31(2): 155-161.

[38]

李伟，董国忠，周艳，等．浅析机器人在猪生产中的应用前景[J]．中国畜牧杂志，2022，58（6）：270-273.

LI Wei, DONG Guozhong, ZHOU Yan, et al. A brief analysis of the application prospects of robots in pig production [J]. China Animal Husbandry Magazine, 2022, 58(6): 270-273.

[39]

沈明霞，刘龙申，闫丽，等．畜禽养殖个体信息监测技术研究进展[J]．农业机械学报，2014，45（10）：245-251.

SHEN Mingxia, LIU Longshen, YAN Li, et al. Research progress in individual information monitoring technology for livestock and poultry breeding [J]. Transactions of the Chinese Society of Agricultural Machinery, 2014, 45(10): 245-251.

[40]

薛鸿翔，沈明霞，刘龙申，等．基于改进YOLO v5s的经产母猪发情检测方法研究[J]．农业机械学报，2023，54（1）：263-270.

XUE Hongxiang, SHEN Mingxia, LIU Longshen, et al. Research on estrus detection method for multiparous sows based on improved YOLO v5s [J]. Transactions of the Chinese Society of Agricultural Machinery, 2023, 54(1): 263-270.

[41]

GILOH M, SHINDER D, YAHAV S. Skin surface temperature of broiler chickens is correlated to body core temperature and is indicative of their thermoregulatory status [J]. Poultry Science, 2012, 91(1): 175-188.

[42]

XUE H, SUN Y, CHEN J, et al. CAT-CBAM-Net: An automatic scoring method for sow body condition based on CNN and transformer [J]. Sensors, 2023, 23(18): 7919.

[43]

毛燕茹，牛童，王鹏，等．利用Kalman滤波和Hungarian算法的多目标奶牛嘴部跟踪及反刍监测[J]．农业工程学报，2021，37（19）：192-201.

MAO Yanru, NIU Tong, WANG Peng, et al. Multi-target cow mouth tracking and rumination monitoring based on Kalman filter and Hungarian algorithm [J]. Transactions of the Chinese Society of Agricultural Engineering, 2021, 37(19): 192-201.

[44]

WANG Y, LI S, ZHANG H, et al. A lightweight CNN-based model for early warning in sow oestrus sound monitoring [J]. Ecological Informatics, 2022, 72: 101863.

[45]

LIU L, ZHOU J, ZHANG B, et al. Visual detection on posture transformation characteristics of sows in late gestation based on Libra R-CNN [J]. Biosystems Engineering, 2022, 223: 219-231.

[46]

SCHAEFER A, VON GAZA H, COOK N, et al. PSXVII-38 Metabolic efficiency in swine determined with automated real time infrared thermography [J]. Journal of Animal Science, 2018, 96(Suppl 3): 146.

[47]

姚文，邓为，许毅，等．家禽亚健康状态监测与健康预警展望[J]．南京农业大学学报，2023，46（4）：635-644.

YAO Wen, DENG Wei, XU Yi, et al. Monitoring of subhealth status and health warning of poultry [J]. Journal of Nanjing Agricultural University, 2023, 46 (4): 635-644.

[48]

MONTEIRO A, SANTOS S, GONÇALVES P. Precision agriculture for crop and livestock farming—Brief review [J]. Animals, 2021, 11(8): 2345.

[49]

袁超，沈明霞，姚文，等．基于发声特征和深度学习的白羽肉鸡全生命周期咳嗽检测方法[J]．南京农业大学学报，2023，46（5）：975-985.

YUAN Chao, SHEN Mingxia, YAO Wen, et al. Cough detection method for white-feathered broiler chickens throughout their life cycle based on vocalization features and deep learning [J]. Journal of Nanjing Agricultural University, 2023, 46(5): 975-985.

[50]

许志强，沈明霞，刘龙申，等．基于红外热图像的肉鸡腿部异常检测方法[J]．南京农业大学学报，2021，44（2）：384-393.

XU Zhiqiang, SHEN Mingxia, LIU Longshen, et al. Broiler leg abnormality detection method based on infrared thermal image [J]. Journal of Nanjing Agricultural University, 2021, 44(2): 384-393.

[51]

沈明霞，王梦雨，刘龙申，等．基于深度神经网络的猪咳嗽声识别方法[J]．农业机械学报，2022，53（5）：257-266.

SHEN Mingxia, WANG Mengyu, LIU Longshen, et al. Pig cough sound recognition method based on deep neural network [J]. Transactions of the Chinese Society of Agricultural Machinery, 2022, 53(5): 257-266.

[52]

WU D, WU Q, YIN X, et al. Lameness detection of dairy cows based on the YOLOv3 deep learning algorithm and a relative step size characteristic vector [J]. Biosystems Engineering, 2020, 189: 150-163.

[53]

BANAKAR A, SADEGHI M, SHUSHTARI A. An intelligent device for diagnosing avian diseases: Newcastle, infectious bronchitis, avian influenza [J]. Computers and Electronics in Agriculture, 2016, 127: 744-753.

[54]

陈佳，丁奇安，刘龙申，等．基于YOLO v5与短时跟踪的鸡只呼吸道疾病早期检测[J]．农业机械学报，2023，54（1）：271-279.

CHEN Jia, DING Qi'an, LIU Longshen, et al. Early detection of respiratory diseases in chickens based on YOLO v5 and short-term tracking [J]. Transactions of the Chinese Society of Agricultural Machinery, 2023, 54(1): 271-279.

[55]

XIN H, BERRY I L, BARTON T L, et al. Feeding and drinking patterns of broilers subjected to different feeding and lighting programs [J]. Journal of Applied Poultry Research, 1993, 2(4): 365-372.

[56]

龙长江，谭鹤群，朱明，等．畜禽舍移动式智能监测平台研制[J]．农业工程学报，2021，37（7）：68-75.

LONG Changjiang, TAN Hequn, ZHU Ming, et al. Development of a mobile intelligent monitoring platform for livestock and poultry houses [J]. Transactions of the Chinese Society of Agricultural Engineering, 2021, 37(7): 68-75.

[57]

PEREIRA W F, DA SILVA FONSECA L, PUTTI F F, et al. Environmental monitoring in a poultry farm using an instrument developed with the Internet of Things concept [J]. Computers and electronics in agriculture, 2020, 170: 105257.

[58]

崔琼，刘勇，徐顺来．猪舍环境的多参数无模型自适应控制算法设计[J]．华南农业大学学报，2024，45（5）：702-708.

CUI Qiong, LIU Yong, XU Shunlai. Design of multi-parameter model-free adaptive control algorithm for pig house environment [J]. Journal of South China Agricultural University, 2024, 45(5): 702-708.

[59]

李嘉豪．猪舍环境智能巡检与监控机器人系统研究[D]．赣州：江西理工大学，2022.

LI Jiahao. Research on intelligent inspection and monitoring robot system for pig house environment [D]. Ganzhou: Jiangxi University of Science and Technology, 2022.

[60]

王恩宇，苏永屹，于浦，等．基于CFD与TRNSYS的圆形猪舍内环境控制研究[J]．黑龙江畜牧兽医，2024，（10）：47-54，112.

WANG Enyu, SU Yongyi, YU Pu, et al. Research on environmental control of circular pig houses based on CFD and TRNSYS [J]. Heilongjiang Animal Husbandry and Veterinary Medicine, 2024(10): 47-54, 112.

[61]

DOERFLER R L, MARTIN R, BERNHARDT H. Implications of robotic walkway cleaning for hoof disorders in dairy cattle [J]. International Journal of Engineering Research and Application, 2017, 7(1): 98-104.

[62]

史文杰．气液一体式猪舍消毒喷雾机的研制与试验[D]．泰安：山东农业大学，2023.

SHI Wenjie. Development and experiment of gas-liquid integrated pig house disinfection sprayer [D]. Tai'an: Shandong Agricultural University, 2023.

[63]

樊士冉，张志勇，李远伟，等．畜牧业有限空间清洗作业机器人设计与研究[J]．黑龙江畜牧兽医，2023（17）：55-60.

FAN Shiran, ZHANG Zhiyong, LI Yuanwei, et al. Design and research of limited space cleaning robot for animal husbandry [J]. Heilongjiang Animal Husbandry and Veterinary Medicine, 2023(17): 55-60.

[64]

刘凯歌．基于DEM-CFD耦合的猪舍高压清洗机器人关键技术研究[D]．杭州：浙江科技大学，2024.

LIU Kaige. Research on key technologies of pig house high pressure cleaning robot based on DEM-CFD coupling [D]. Hangzhou: Zhejiang University of Science and Technology, 2024.

[65]

EBERTZ P, KROMMWEH M S, BÜSCHER W. Feasibility study: improving floor cleanliness by using a robot scraper in group-housed pregnant sows and their reactions on the new device [J]. Animals, 2019, 9(4): 185.

[66]

FENG Q, WANG B, ZHANG W, et al. Development and test of spraying robot for anti-epidemic and disinfection in animal housing [C] //2021 WRC Symposium on Advanced Robotics and Automation (WRC SARA). IEEE, 2021: 24-29.

[67]

赵文文，王海峰，朱君，等．猪舍消杀巡检机器人系统设计与试验[J]．农业机械学报，2022，53（S2）：270-277.

ZHAO Wenwen, WANG Haifeng, ZHU Jun, et al. Design and experiment of pig house disinfection inspection robot system [J]. Transactions of the Chinese Society of Agricultural Machinery, 2022, 53(S2): 270-277.

[68]

柳忠魁．国内外奶牛挤奶设备综述[J]．粮油加工与食品机械，1984（4）：1-9.

LIU Zhongkui. Overview of domestic and foreign dairy cow milking equipment [J]. Grain and Oil Processing and Food Machinery, 1984(4): 1-9.

[69]

于燚，李鑫．挤奶设备终端发展概况[J]．中国奶牛，2022（6）：38-43.

YU Yi, LI Xin. Overview of the development of milking equipment terminals [J]. China Dairy, 2022(6): 38-43.

[70]

GEA．GEA DairyRobot R9500机器人挤奶系统[EB/OL]．https://www.gea.com/zh/products/milking-farming-barn/dairyrobot-automated-milking/dairyrobot-r9500-robotic-milking-system, 2022-10-10.

[71]

MILKOMAX. Milking robot-milkomax solutions laitières[EB/OL]. https://milkomax.com/en/milking-robot, 2020-01-31.

[72]

李硕．七自由度挤奶机器人的设计与研究[D]．淮南：安徽理工大学，2023.

LI Shuo. Design and research of seven-degree-of-freedom milking robot [D]. Huainan: Anhui University of Science and Technology, 2023.

[73]

高继伟，李彩琴，庞建建，等．9JZP-80高效转盘式挤奶机的研发与应用[J]．黑龙江畜牧兽医，2022（12）：50-55，127-129.

GAO Jiwei, LI Caiqin, PANG Jianjian, et al. Research and development and application of 9JZP-80 high-efficiency rotary milking machine [J]. Heilongjiang Animal Husbandry and Veterinary Medicine, 2022(12): 50-55, 127-129.

[74]

CHANG C L, XIE B X, WANG C H. Visual guidance and egg collection scheme for a smart poultry robot for free-range farms [J]. Sensors, 2020, 20(22): 6624.

[75]

JOFFE B P, USHER C T. Autonomous robotic system for picking up floor eggs in poultry houses [C]// 2017 ASABE Annual International Meeting. American Society of Agricultural and Biological Engineers, 2017.

[76]

VROEGINDEWEIJ B A, BLAAUW S K, IJSSELMUIDEN J M M, et al. Evaluation of the performance of PoultryBot, an autonomous mobile robotic platform for poultry houses [J]. Biosystems Engineering, 2018, 174: 295-315.

[77]

苑进，李扬，刘雪美，等．禽蛋自动捡拾系统结构设计及机械手运动规划[J]．农业工程学报，2016，32（8）：48-55.

YUAN Jin, LI Yang, LIU Xuemei, et al. Structural design of automatic egg picking system and manipulator motion planning [J]. Transactions of the Chinese Society of Agricultural Engineering, 2016, 32(8): 48-55.

[78]

李伟，董国忠，周艳，等．浅析机器人在猪生产中的应用前景[J]．中国畜牧杂志，2022，58（6）：270-273.

LI Wei, DONG Guozhong, ZHOU Yan, et al. A brief analysis of the application prospects of robots in pig production [J]. China Animal Husbandry Magazine, 2022, 58(6): 270-273.

[79]

SVEAVERKEN. RoboPusher Pro[EB/OL]. https://www.sveaverken.com/products/robopusher-pro, 2024-05-31.

[80]

赵大庆，管延华，齐自成，等．生猪液态饲料智能喂料车设计与试验[J]．中国农机化学报，2022，43（12）：91-98.

ZHAO Daqing, GUAN Yanhua, QI Zicheng, et al. Design and experiment of intelligent feeding vehicle for liquid feed of pigs [J]. Journal of Chinese Agricultural Mechanization, 2022, 43(12): 91-98.

[81]

唐诗杰，谷月，李传珍，等．基于EDEM的笼养种鸭精准饲喂器的设计与试验[J]．华中农业大学学报，2024，43（5）：269-277.

TANG Shijie, GU Yue, LI Chuanzhen, et al. Design and experiment of precision feeder for caged breeder ducks based on EDEM [J]. Journal of Huazhong Agricultural University, 2024, 43(5): 269-277.

[82]

闫银发，刘冠鲁，宋占华，等．精准配比料药一体化生猪饲喂器设计与试验[J]．农业机械学报，2023，54（S2）：142-149.

YAN Yinfa, LIU Guanlu, SONG Zhanhua, et al. Design and experiment of pig feeder with integrated precise feed and medicine ratio [J]. Transactions of the Chinese Society of Agricultural Machinery, 2023, 54(S2): 142-149.

[83]

王鑫杰．基于机器视觉的奶牛个体进食信息自动监测方法研究[D]．哈尔滨：东北农业大学，2023.

WANG Xinjie. Research on automatic monitoring method of individual cow eating information based on machine vision [D]. Harbin: Northeast Agricultural University, 2023.

[84]

ZUIDHOF M J, FEDORAK M V, OUELLETTE C A, et al. Precision feeding: Innovative management of broiler breeder feed intake and flock uniformity [J]. Poultry Science, 2017, 96(7): 2254-2263.

[85]

LELY. Lely Vector[EB/OL]. https://www.lely.com/solutions/feeding/vector/, 2019-10-30.

[86]

李波．基于巡检机器人的母猪体尺智能检测系统研究[D]．南京：南京农业大学，2022.

LI Bo. Research on intelligent detection system of sow body size based on inspection robot [D]. Nanjing: Nanjing Agricultural University, 2022.

[87]

EDWARDS D J, AKHTAR J, RILLIE I, et al. Systematic analysis of driverless technologies [J]. Journal of Engineering, Design and Technology, 2022, 20(6): 1388-1411.

[88]

KING A J, PORTUGAL S J, STRÖMBOM D, et al. Biologically inspired herding of animal groups by robots [J]. Methods in Ecology and Evolution, 2023, 14(2): 478-486.

[89]

PARANJAPE A A, CHUNG S J, KIM K, et al. Robotic herding of a flock of birds using an unmanned aerial vehicle [J]. IEEE Transactions on Robotics, 2018, 34(4): 901-915.

[90]

TREVELYAN J P. Robots in the shearing shed: Automated shearing of sheep using robots [J]. Advanced Robotics, 1987, 2(1): 3-8.

[91]

田儒雅，王红彦，孙巍，等．2023中国农业科技论文与专利全球竞争力分析[J]．农学学报，2024，14（3）：10-12.

TIAN Ruya, WANG Hongyan, SUN Wei, et al. Analysis on the global competitiveness of China's agricultural science and technology papers and patents in 2023 [J]. Acta Agronomica Sinica, 2024, 14(3): 10-12.

[92]

KBV RESEARCH. KBV reGlobal Agricultural Robots Market Size, Share & Industry Trends Analysis Report 2023-2030[R/OL]. https://www.kbvresearch.com/agricultural-robots-market/, 2023-10.

2025年第6卷第2期

预览PDF | 下载PDF

引用本文

BibTeX

文章信息

doi: 10.12398/j.issn.2096-7217.2025.02.004

接收时间：2024-09-18
首发时间：2026-11-05
出版时间：2025-05-15

补充材料

相关文章

文章信息

作者

出版历史

收稿日期：2024-09-18
修回日期：2024-12-05

基金

National Key Research and Development Program of China(2021YFD2000800)

国家重点研发计划(2021YFD2000800)

作者信息

^1.南京农业大学工学院，江苏南京，210031

^2.农业农村部养殖装备重点实验室，江苏南京，210031

^3.南京农业大学人工智能学院，江苏南京，210031

^4.马辛德穆利罗科技大学，肯尼亚卡卡梅加，190-50100

通讯作者:

^* 沈明霞，女，1964年生，江苏常熟人，博士，教授，博导；研究方向为机器视觉与信息农业。E-mail：mingxia@njau.edu.cn

参考文献

分享链接

https://castjournals.cast.org.cn/joweb/znhnyzbxb/CN/10.12398/j.issn.2096-7217.2025.02.004

分享至

全文二维码

扫描看全文

引用本文

BibTeX

本文的引用情况

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

关闭全屏

BibTeX
EndNote
RefWorks
TxT