智能化农业装备学报（中英文）

设施农业自主移动装备导航技术研究进展

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黄银锋 ¹ , 孙国祥 ¹^,²^,^*^,^* , 汪小旵 ¹^,² , 施印炎 ¹^,² , 章永年 ¹^,² , 陈光宇 ¹

智能化农业装备学报（中英文） | 2025,6(4): 1-16

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智能化农业装备学报（中英文） | 2025 , 6 (4) : 1 -16

设施农业自主移动装备导航技术研究进展

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黄银锋¹, 孙国祥¹^,²^,^*^,^*, 汪小旵¹^,², 施印炎¹^,², 章永年¹^,², 陈光宇¹

作者信息

^1.南京农业大学工学院，江苏南京，210031

^2.江苏省现代设施农业技术与装备实验室，江苏南京，210031

通讯作者:

^* 孙国祥，男，1985年生，江苏盐城人，博士，副教授；研究方向为设施园艺智能化装备。E-mail：sguoxiang@njau.edu.cn

作者简介:

黄银锋，男，1998年生，江苏泰州人，硕士研究生；研究方向为农业机器人。E-mail：2021112038@stu.njau.edu.cn

Research progress in navigation technology for autonomous mobile equipment in facility agriculture

Yinfeng HUANG¹, Guoxiang SUN¹^,², Xiaochan WANG¹^,², Yinyan SHI¹^,², Yongnian ZHANG¹^,², Guangyu CHEN¹

Affiliations

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

^2.Jiangsu Province Engineering Lab for Modern Facility Agriculture Technology & Equipment, Nanjing 210031, China

Corresponding Author:

^* SUN Guoxiang, E-mail: sguoxiang@njau.edu.cn

HUANG Yinfeng, E-mail: 2021112038@stu.njau.edu.cn

出版时间: 2025-11-15 doi: 10.12398/j.issn.2096-7217.2025.04.001

文章导航

摘要

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设施农业自主移动装备导航技术的研发对于设施农业的智能化升级具有举足轻重的意义，其面临的核心挑战在于如何在设施场景内部实现安全、高效和精确的移动。通过深入剖析国内外最新的研究动态，本研究旨在全面阐述设施农业自主移动装备导航技术的发展脉络，并探讨其未来的发展趋势。首先梳理了设施农业自主移动装备导航技术的研究现状，重点分析了不同导航方式的优缺点，包括导轨式、循迹式以及基于实时定位与地图构建（simultaneous localization and mapping，SLAM）技术的多源数据融合导航。在此基础上，进一步探讨了基于SLAM技术的多源数据融合导航在实时定位、地图构建以及路径规划等方面的最新研究进展。相关研究表明，传统的导轨式和循迹式导航方式虽然简单易行，但存在路线固定、安装成本高、作业范围受限等问题。相比之下，基于SLAM技术的多源数据融合导航则具有更高的灵活性和自主性，能够实现精准定位、智能避障以及自适应路径规划等功能，因此在设施农业自主移动装备领域具有广阔的应用前景。随着SLAM技术的不断发展和完善，基于多源数据融合导航的设施农业自主移动装备将迎来更加广阔的发展空间。同时，本研究也关注到这些技术在实际应用中可能存在的挑战和限制，如数据处理能力、算法优化等问题。最后，对我国设施农业自主移动装备导航技术的研发提出了几点展望：采用多源数据融合式导航技术，实现高精度定位与地图构建；引入人工智能、云计算与边缘计算等技术，提升自主移动装备对于复杂设施场景的识别和理解能力；通过全局路径规划和局部路径规划相结合，实现自主移动装备的自主决策和路径规划；通过智能避障技术，提高自主识别和避让障碍物能力，确保作业过程中的安全性与可靠性；深入研究多机协同、人机协同的自主移动装备，实现多任务协同作业，提升装备适用性和作业效率。该研究旨在为我国设施农业自主移动装备智能化发展提供有益的参考和借鉴。

关键词

设施农业 / 导航 / 自主移动装备 / 实时定位 / 地图构建 / 路径规划

Abstract

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The development of navigation technologies for autonomous mobile equipment is pivotal to the intelligent upgrading of facility agriculture, with its core challenge being how to achieve safe, efficient, and precise movement within greenhouse environments. Through an in-depth analysis of the latest research trends, this study aims to comprehensively elucidate the evolution of these navigation technologies and discuss their future directions. We begin by reviewing the state of the art, with a focus on comparing the advantages and disadvantages of different navigation methods, including guide-rail, path-tracking, and multi-source data fusion navigation based on simultaneous localization and mapping (SLAM) technology. Furthermore, we explore recent advances in SLAM-based multi-source data fusion navigation for real-time localization, mapping, and path planning. Relevant research indicates that while traditional guide-rail and path-tracking methods are simple to implement, they suffer from fixed routes, high installation costs, and limited operational range. In contrast, SLAM-based multi-source data fusion navigation offers greater flexibility and autonomy, enabling precise localization, intelligent obstacle avoidance, and adaptive path planning, thus holding broad application prospects in facility agriculture. As SLAM technology continues to mature, equipment employing this navigation approach will see even wider adoption. This study also addresses practical challenges and limitations, such as computational demands and algorithm optimization. Finally, we propose several development prospects for China's facility agriculture: adopting multi-source data fusion navigation to achieve high-precision localization and mapping; integrating artificial intelligence, cloud computing, and edge computing to enhance the equipment's perception and understanding of complex environments; combining global and local path planning to enable autonomous decision-making; implementing intelligent obstacle avoidance to ensure operational safety and reliability; and investigating multi-vehicle and human-vehicle collaboration for efficient multi-task coordination. This research aims to provide valuable insights and references for the intelligent development of autonomous mobile equipment in Chinese facility agriculture.

Key words

facility agriculture / navigation / autonomous walking equipment / real-time positioning / map construction / path planning

引用本文

黄银锋, 孙国祥, 汪小旵, 施印炎, 章永年, 陈光宇. 设施农业自主移动装备导航技术研究进展. 智能化农业装备学报（中英文）, 2025 , 6 (4) : 1 -16 . DOI: 10.12398/j.issn.2096-7217.2025.04.001

Yinfeng HUANG, Guoxiang SUN, Xiaochan WANG, Yinyan SHI, Yongnian ZHANG, Guangyu CHEN. Research progress in navigation technology for autonomous mobile equipment in facility agriculture[J]. Journal of Intelligent Agricultural Mechanization, 2025 , 6 (4) : 1 -16 . DOI: 10.12398/j.issn.2096-7217.2025.04.001

基金

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国家重点研发计划项目(2023YFD2000304; 2023YFD2000305)
江苏省农业科技自主创新资金项目(CX（22）3097)
江苏省现代农机装备与技术示范推广项目(NJ2023-44)

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2025年第6卷第4期

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doi: 10.12398/j.issn.2096-7217.2025.04.001

接收时间：2024-05-16
首发时间：2026-11-05
出版时间：2025-11-15

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收稿日期：2024-05-16
修回日期：2024-06-28

基金

National Key Research and Development Program of China(2023YFD2000304; 2023YFD2000305)

国家重点研发计划项目(2023YFD2000304; 2023YFD2000305)

Jiangsu Agricultural Science and Technology Innovation Fund(CX（22）3097)

江苏省农业科技自主创新资金项目(CX（22）3097)

Jiangsu Modern Agricultural Machinery Equipment and Technology Demonstration and Promotion Project(NJ2023-44)

江苏省现代农机装备与技术示范推广项目(NJ2023-44)

作者信息

^1.南京农业大学工学院，江苏南京，210031

^2.江苏省现代设施农业技术与装备实验室，江苏南京，210031

通讯作者:

^* 孙国祥，男，1985年生，江苏盐城人，博士，副教授；研究方向为设施园艺智能化装备。E-mail：sguoxiang@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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