智能化农业装备学报(中英文) ›› 2025, Vol. 6 ›› Issue (2): 1-23.DOI: 10.12398/j.issn.2096-7217.2025.02.001
• •
收稿日期:
2025-03-04
修回日期:
2025-04-02
出版日期:
2025-05-15
发布日期:
2025-05-20
通讯作者:
汪小旵
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
基金资助:
WANG Dezhi(), WANG Yanxin, WANG Xiaochan(
), SHI Yinyan, ZHANG Yongnian
Received:
2025-03-04
Revised:
2025-04-02
Online:
2025-05-15
Published:
2025-05-20
Contact:
WANG Xiaochan
About author:
WANG Dezhi, E-mail: 2024212004@stu.njau.edu.cn
Supported by:
摘要:
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。
中图分类号:
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[J]. 智能化农业装备学报(中英文), 2025, 6(2): 1-23.
WANG Dezhi, WANG Yanxin, WANG Xiaochan, SHI Yinyan, ZHANG Yongnian. Management and harvesting technologies in agricultural robotics: Current status, challenges and future developments[J]. Journal of Intelligent Agricultural Mechanization, 2025, 6(2): 1-23.
机器人类型 | 作业任务 | 关键技术 | 优点 | 缺点 |
---|---|---|---|---|
信息采集机器人 | 收集土壤理化性质、气象变化、作物生长及病虫害等数据 | 多传感器融合、数据处理、自主导航 | 获取多维度数据,为精准农业提供决策依据;提高数据采集效率和准确性 | 复杂环境下传感器易受干扰;数据处理与分析难度大 |
授粉机器人 | 实现作物授粉自动化,提高授粉效率和果实质量 | 花朵识别与定位、末端执行器设计与控制、自主导航 | 提高授粉效率和产量;避免病害传播风险 | 不同花期花朵识别难度大;末端执行器授粉方式有限 |
除草机器人 | 识别和清除农田中的杂草 | 作物与杂草识别、路径规划、杂草清除操作 | 减少农药使用;降低杂草竞争,提高作物产量 | 作物与杂草识别准确率受环境影响;部分除草方式有可能损伤作物 |
植保机器人 | 自动精准完成病虫害防治、农药喷洒等任务 | 病虫害识别、农药精准喷洒、自主导航 | 精准施药,减少农药浪费;有效控制病虫害扩散 | 病虫害识别精度有待提高;农药喷洒均匀性和覆盖性需优化 |
打叶整枝机器人 | 根据植物生长状态进行打叶整枝操作 | 枝叶识别与定位、作业执行机构设计与控制、路径规划 | 促进植物生长;提高光照和空气流通 | 不同作物枝叶形态位姿估计算法复杂;作业执行机构设计难度大 |
表1 农业管理机器人对比分析
Table 1 Comparative analysis of agricultural management robots
机器人类型 | 作业任务 | 关键技术 | 优点 | 缺点 |
---|---|---|---|---|
信息采集机器人 | 收集土壤理化性质、气象变化、作物生长及病虫害等数据 | 多传感器融合、数据处理、自主导航 | 获取多维度数据,为精准农业提供决策依据;提高数据采集效率和准确性 | 复杂环境下传感器易受干扰;数据处理与分析难度大 |
授粉机器人 | 实现作物授粉自动化,提高授粉效率和果实质量 | 花朵识别与定位、末端执行器设计与控制、自主导航 | 提高授粉效率和产量;避免病害传播风险 | 不同花期花朵识别难度大;末端执行器授粉方式有限 |
除草机器人 | 识别和清除农田中的杂草 | 作物与杂草识别、路径规划、杂草清除操作 | 减少农药使用;降低杂草竞争,提高作物产量 | 作物与杂草识别准确率受环境影响;部分除草方式有可能损伤作物 |
植保机器人 | 自动精准完成病虫害防治、农药喷洒等任务 | 病虫害识别、农药精准喷洒、自主导航 | 精准施药,减少农药浪费;有效控制病虫害扩散 | 病虫害识别精度有待提高;农药喷洒均匀性和覆盖性需优化 |
打叶整枝机器人 | 根据植物生长状态进行打叶整枝操作 | 枝叶识别与定位、作业执行机构设计与控制、路径规划 | 促进植物生长;提高光照和空气流通 | 不同作物枝叶形态位姿估计算法复杂;作业执行机构设计难度大 |
机器人类型 | 关键技术 | 优点 | 缺点 |
---|---|---|---|
水果采摘 机器人 | 果实识别与定位、末端执行器设计与控制、导航与路径规划 | 提高采摘效率 | 果实识别准确率受遮挡和成熟度影响;末端执行器对不同水果适应性有限 |
蔬菜采摘 机器人 | 视觉识别、运动规划、末端执行器控制 | 实现高效采摘; 人工劳动强度 | 对复杂环境适应性较弱;部分蔬菜采摘难度大,易造成损伤 |
食用菌采摘机器人 | 目标检测与定位、柔性末端执行器设计 | 提高采摘效率和质量 | 对食用菌生长环境要求较高,识别难度大 |
花卉采摘 机器人 | 视觉定位、机械臂运动控制 | 保证花卉采摘质量; 提高采摘效率 | 对花卉形态和生长环境要求较高 |
名优茶采摘机器人 | 茶叶识别与定位、采摘路径规划、末端执行器设计 | 提高采摘效率; 保证茶叶品质 | 茶叶生长环境复杂,对茶叶嫩芽识别精度要求高 |
表2 农业采摘机器人对比分析
Table 2 Comparative analysis of agricultural harvesting robots
机器人类型 | 关键技术 | 优点 | 缺点 |
---|---|---|---|
水果采摘 机器人 | 果实识别与定位、末端执行器设计与控制、导航与路径规划 | 提高采摘效率 | 果实识别准确率受遮挡和成熟度影响;末端执行器对不同水果适应性有限 |
蔬菜采摘 机器人 | 视觉识别、运动规划、末端执行器控制 | 实现高效采摘; 人工劳动强度 | 对复杂环境适应性较弱;部分蔬菜采摘难度大,易造成损伤 |
食用菌采摘机器人 | 目标检测与定位、柔性末端执行器设计 | 提高采摘效率和质量 | 对食用菌生长环境要求较高,识别难度大 |
花卉采摘 机器人 | 视觉定位、机械臂运动控制 | 保证花卉采摘质量; 提高采摘效率 | 对花卉形态和生长环境要求较高 |
名优茶采摘机器人 | 茶叶识别与定位、采摘路径规划、末端执行器设计 | 提高采摘效率; 保证茶叶品质 | 茶叶生长环境复杂,对茶叶嫩芽识别精度要求高 |
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