智能化农业装备学报（中英文）

丘陵山区低空飞行农业装备应用场景、发展现状及对策建议——以四川省为例

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李秋实 ¹^,² , 江启峰 ¹ , 刘环宇 ¹^,^*^,^* , 唐立 ¹ , 杜海 ¹ , 郎方年 ¹ , 陶智 ²

智能化农业装备学报（中英文） | 2026,7(2): 37-50

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智能化农业装备学报（中英文） | 2026 , 7 (2) : 37 -50

丘陵山区低空飞行农业装备应用场景、发展现状及对策建议——以四川省为例

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李秋实¹^,², 江启峰¹, 刘环宇¹^,^*^,^*, 唐立¹, 杜海¹, 郎方年¹, 陶智²

作者信息

^1.西华大学，四川成都，610039

^2.北京航空航天大学，北京市，100191

通讯作者:

^* 刘环宇，男，1990年生，黑龙江哈尔滨人，博士，副教授；研究方向为低空飞行农业装备、农机自主作业关键技术。E-mail：liuhy0528@163.com

作者简介:

李秋实，男，1970年生，重庆人，博士，教授；研究方向为航空发动机气动力学、低空飞行农业装备。E-mail：liqs@xhu.edu.cn

Application scenarios, development status, and countermeasures for low-altitude aerial agricultural equipment in hilly region: a case study of Sichuan Province

Qiushi Li¹^,², Qifeng Jiang¹, Huanyu Liu¹, Li Tang¹, Hai Du¹, Fangnian Lang¹, Zhi Tao²

Affiliations

^1.Xihua University, Chengdu 610039, China

^2.Beihang University, Beijing 100191, China

Corresponding Author:

^* Liu Huanyu, E-mail: liuhy0528@163.com

Li Qiushi, E-mail: liqs@mail.xhu.edu.cn

出版时间: 2026-05-15 doi: 10.12398/j.issn.2096-7217.2026.02.004

文章导航

摘要

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低空飞行农业装备作为低空经济与农业农村融合发展的关键载体，对打造农业新质生产力、构建现代农业生产体系、保障国家粮食安全具有重要战略意义。系统梳理低空飞行农业装备在四川丘陵山区的应用场景与存在问题，阐述四川丘陵山区多种低空农业装备及其配套动力、智能控制与管理技术体系，分析智能植保与精准施药、低空遥感与农情监测、农资与农产品转运、播种施肥与授粉作业、应急保障与物流配送等应用场景，重点剖析其在丘陵山区装备研发制造、智能化作业技术、作业运维等3方面所面临的问题与挑战。从关键技术攻关层面，提出开展全程机械化、智能化作业体系模式与成套装备作业平台集成验证，创制“空天地”一体丘陵山区农机协同作业系统试验验证方法；从智能、绿色、安全3个方面进一步明确低空飞行农业装备技术的发展要求；从优化创新生态体系层面，提出健全人才引进培养机制，构建“平台支撑—人才保障—产业协同”三位一体的产学研发展体系，形成良性循环的低空农业装备产业创新体系，全面提升丘陵山区农机装备科技水平和产业竞争力。通过在四川等典型丘陵山区布局建立全程机械化示范区，开展装备试验验证与技术熟化，加强基层操作人员培训，为形成可复制推广的丘陵山区农业机械化整体解决方案提供方向指南。

关键词

丘陵山区 / 低空经济 / 低空飞行农业装备 / 人工智能 / 应用场景

Abstract

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The deep integration of the low-altitude economy with agricultural and rural development is of strategic importance for enhancing comprehensive competitiveness, building a modern agricultural production system, and strengthening national food security. This study systematically reviews the application scenarios and existing challenges of low-altitude aircraft in the hilly and mountainous regions of Sichuan Province. It elaborates on the various low-altitude carrier platforms and their supporting power systems, as well as the intelligent control and management technology systems deployed in these regions. The study analyzes application scenarios including intelligent plant protection and precision pesticide application, low-altitude remote sensing and agricultural condition monitoring, transportation of agricultural inputs and products, seeding, fertilization, and pollination operations, as well as emergency support and logistics distribution. Furthermore, it identifies the issues and challenges faced by low-altitude carrier platforms in the hilly regions across three key aspects: equipment R&D and manufacturing, intelligent operational technologies, and operation and maintenance. From the perspective of critical technology breakthroughs, it proposes conducting integrated validation of models for full-process mechanized and intelligent systems alongside complete equipment sets. It also suggests developing a testing and validation method for “air-space-ground” integrated collaborative operation system for agricultural machinery in hilly regions. From the three dimensions of intelligence, greenness, and safety, it further clarifies the development requirements for low-altitude agricultural aviation equipment technology. From the perspective of optimizing the innovation ecosystem, it proposes improving mechanisms for talent introduction and cultivation, establishing a “platform support-talent guarantee-industry collaboration” trinity industry-university-research development system, and forming a virtuous-cycle innovation system for the low-altitude agricultural equipment industry. This approach aims to comprehensively enhance the technological level and industrial competitiveness of agricultural machinery in hilly regions. By establishing full-process mechanization demonstration zones in typical hilly regions such as Sichuan Province, conducting equipment validation and technology maturation, and strengthening training for grassroots operators, it provides directional guidance for developing replicable and scalable integrated solutions for agricultural mechanization in hilly regions.

Key words

hilly region / low-altitude economy / low-altitude aerial agricultural equipment / artificial intelligence / application scenarios

引用本文

李秋实, 江启峰, 刘环宇, 唐立, 杜海, 郎方年, 陶智. 丘陵山区低空飞行农业装备应用场景、发展现状及对策建议——以四川省为例. 智能化农业装备学报（中英文）, 2026 , 7 (2) : 37 -50 . DOI: 10.12398/j.issn.2096-7217.2026.02.004

Qiushi Li, Qifeng Jiang, Huanyu Liu, Li Tang, Hai Du, Fangnian Lang, Zhi Tao. Application scenarios, development status, and countermeasures for low-altitude aerial agricultural equipment in hilly region: a case study of Sichuan Province[J]. Journal of Intelligent Agricultural Mechanization, 2026 , 7 (2) : 37 -50 . DOI: 10.12398/j.issn.2096-7217.2026.02.004

基金

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国家自然科学基金区域联合基金项目(U24A20141)
国家自然科学基金项目(32501805; 52102384)

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]

邹一南，吴晓宇，张焕．《加快建设农业强国规划（2024—2035年）》搭建统领“三农”工作的战略总纲[J]．农村金融研究，2025（5）：3-14.

Zou Yinan, Wu Xiaoyu, Zhang Huan. "Plan to Accelerate Building Up China′s Strength in Agriculture (2024-2035)": a strategic framework for coordinating issues relating to agriculture, rural areas, and farmers [J]. Rural Finance Research, 2025(5): 3-14.

[2]

崔思远，曹蕾，陈聪，等．基于应用场景的丘陵山区农业机械化发展路径研究[J]．智能化农业装备学报（中英文），2024，5（2）：1-8.

Cui Siyuan, Cao Lei, Chen Cong, et al. Path research on the agricultural mechanization development in hilly and mountainous areas based on application scenarios [J]. Journal of Intelligent Agricultural Mechanization, 2024, 5(2): 1-8.

[3]

达州市人民政府．全国丘陵山区现代农机产业投资推介会（四川·达州）暨智能制造产业项目集中签约仪式[EB/OL]．（2024-08-26）[2025-12-19]．https://www.dazhou.gov.cn/news-show-256010.html.

[4]

贵州省人民政府．关于政协第十四届全国委员会第二次会议第02892号（农业水利类209号）提案会办意见的函[EB/OL]．（2024-10-22）[2025-12-19]．https://www.guizhou.gov.cn/ztzl/jyta/blfw/qgjyta/2024n/qgzxta/202410/t20241022_85965707.html.

[5]

胡志超，张萌，罗伟文，等．加快中国丘陵山区农机化发展的思考与对策[J]．农业工程学报，2025，41（14）：39-50.

Hu Zhichao, Zhang Meng, Luo Weiwen, et al. Advancing agricultural mechanization in China′s hilly and mountainous areas: key strategies and technological focus [J]. Transactions of the Chinese Society of Agricultural Engineering, 2025, 41(14): 39-50.

[6]

王健，张辉，沈玉君，等．中国循环农业发展实践与推进路径探究[J]．农业工程学报，2024，40（22）：12-21.

Wang Jian, Zhang Hui, Shen Yujun, et al. Development practice and promotion route of circular agriculture in China[J]. Transactions of the Chinese Society of Agricultural Engineering, 2024, 40(22): 12-21.

[7]

倪鼎文，康辉，赵世界，等．农业新质生产力赋能农业绿色生产效率的内在机理与实证检验[J]．福建农林大学学报（哲学社会科学版），2025，28（6）：36-53.

Ni Dingwen, Kang Hui, Zhao Shijie, et al. The internal mechanism and empirical test of new quality productive forces empowering agricultural green production efficiency[J]. Journal of Fujian Agriculture and Forestry University(Philosophy and Social Sciences), 2025, 28(6): 36-53.

[8]

周昊天，段小梅．中国式现代化视域下农业新质生产力：理论审视、价值意蕴与未来进路[J]．重庆工商大学学报（社会科学版），2025，42（1）：54-64.

Zhou Haotian, Duan Xiaomei. New quality agricultural productive forces in the perspective of Chinese-style modernization: theoretical review, value implication, and future pathway [J]. Journal of Chongqing Technology and Business University (Social Science Edition), 2025, 42(1): 54-64.

[9]

闫全涛，李丽霞，邱权，等．小型农田原状土样采集机器人系统研发与测试[J]．智能化农业装备学报（中英文），2024，5（1）：12-22.

Yan Quantao, Li Lixia, Qiu Quan, et al. Development and test of a small robotic system for in field undisturbed soil sampling [J]. Journal of Intelligent Agricultural Mechanization, 2024, 5(1): 12-22.

[10]

中国新闻网．中国农用无人机保有量超30万架[EB/OL]．（2025-12-31）[2026-01-11]．https://www.chinanews.com/cj/2025/12-31/10543750.shtml.

[11]

张辉洋．油电混动倾转旋翼无人机PWM整流器研究与设计[D]．海口：海南大学，2023.

Zhang Huiyang. Research and design of PWM rectifier for oil-electric hybrid tilting rotor UAV [D]. Haikou: Hainan University, 2023.

[12]

北大荒集团七星农场有限公司．无人机夏管作业实现水稻精准化管护[N/OL]．中国农业机械化信息网，2025-07-21．http://www.amic.agri.cn/secondLevelPage/info/218/206905.

[13]

Walkera．载物无人机厂家，大载重长续航无人机品牌[EB/OL]．（2024-04-25）[2026-01-11]．https://entrance.walkera.com/index.php？id=2097.

[14]

魏堂伟，张津诚，王晶，等．基于改进YOLOv7的茶叶嫩芽识别模型研究[J]．智能化农业装备学报（中英文），2024，5（2）：42-50.

Wei Tangwei, Zhang Jincheng, Wang Jing, et al. Study of tea buds recognition and detection based on improved YOLOv7 model [J]. Journal of Intelligent Agricultural Mechanization, 2024, 5(2): 42-50.

[15]

头豹研究院．低空耕者——农业无人机重塑智慧农耕的新范式与未来图景[R/OL]．[2025-11-13]．https://pdf.dfcfw.com/pdf/H3_AP202511191784411203_1.pdf？1763581726000.

[16]

车海威，张成成，赵树言．无人机动力系统综合控制研究[J]．现代电子技术，2023，46（6）：111-117.

Che Haiwei, Zhang Chengcheng, Zhao Shuyan. Research on integrated control of UAV propulsion system [J]. Modern Electronics Technique, 2023, 46(6): 111-117.

[17]

Cirigliano D, Frisch A M, Liu F, et al. Diesel, spark-ignition, and turboprop engines for long-duration unmanned air flights [J]. Journal of Propulsion and Power, 2018, 34(4): 878-892.

[18]

中国气象局．在希望的田野上丨透过三个田间故事—看四川气象为农服务新风向[EB/OL]．（2025-04-02）[2025-12-19]．https://www.cma.gov.cn/2011xwzx/2011xqxxw/2011xqxyw/202504/t20250402_6970252.html.

[19]

Hua L, Zhang J, Li D, et al. Fault-tolerant active disturbance rejection control of plant protection of unmanned aerial vehicles based on a spatio-temporal RBF neural network[J]. Applied Sciences, 2021, 11(9): 4084.

[20]

Zhu C, Wang Z, Zhang D, et al. Prescribed time backstepping sliding mode control for attitude stabilization of plant-protection UAVs under wind and motor disturbances [J]. Frontiers in Plant Science, 2025, 16: 1689665.

[21]

Chen Z, Liu C, Su H, et al. A hybrid disturbance observer for delivery drone′s oscillation suppression [J]. Mechatronics, 2022, 88: 102907.

[22]

Liu X, Li G, Yang H, et al. Agricultural UAV trajectory planning by incorporating multi-mechanism improved grey wolf optimization algorithm [J]. Expert Systems with Applications, 2023, 233: 120946.

[23]

Liu X, Shao P, Li G, et al. Complex hilly terrain agricultural UAV trajectory planning driven by grey wolf optimizer with interference model [J]. Applied Soft Computing, 2024, 160: 111710.

[24]

Arshid K, Krayani A, Marcenaro L, et al. Toward autonomous UAV swarm navigation: a review of trajectory design paradigms [J]. Sensors, 2025, 25(18): 5877.

[25]

郭旺，杨雨森，吴华瑞，等．农业大模型：关键技术、应用分析与发展方向[J]．智慧农业（中英文），2024，6（2）：1-13.

Guo Wang, Yang Yusen, Wu Huarui, et al. Big models in agriculture: key technologies, application and future directions [J]. Smart Agriculture, 2024, 6(2): 1-13.

[26]

Zhang W, Cai M, Zhang T, et al. EarthMarker: a visual prompting multimodal large language model for remote sensing [J]. IEEE Transactions on Geoscience and Remote Sensing, 2024, 63: 1-19.

[27]

Meng S, Wang Y, Yang C F, et al. Llm-a*: large language model enhanced incremental heuristic search on path planning[C]// Findings of the Association for Computational Linguistics: EMNLP 2024, 2024: 1087-1102.

[28]

Han S, Wan P, Lian Z, et al. Research on the construction and resource optimization of a UAV command information system based on large language models [J]. Drones, 2025, 9(9): 639.

[29]

孙竹，顾伟，崔龙飞，等．智能植保装备关键技术研究现状与发展趋势[J]．智能化农业装备学报（中英文），2024，5（4）：1-23.

Sun Zhu, Gu Wei, Cui Longfei, et al. Research status and development trends of key technologies for intelligent plant protection equipment [J]. Journal of Intelligent Agricultural Mechanization, 2024, 5(4): 1-23.

[30]

李董，汤启国，王红波，等．农作物重大病虫害预警与应急防控技术研究现状与趋势[J]．智能化农业装备学报（中英文），2025，6（1）：25-40.

Li Dong, Tang Qiguo, Wang Hongbo, et al. Current status and trends of research on early warning and emergency control technology for major crop pests and diseases [J]. Journal of Intelligent Agricultural Mechanization, 2025, 6(1): 25-40.

[31]

谭亮华，庞嘉，莫勇，等．湖南攸县杂交水稻全程机械化制种关键技术示范与效果[J]．杂交水稻，2024，39（1）：88-92.

Tan Lianghua, Pang Jia, Mo Yong, et al. Demonstration and results of key techniques for whole-process mechanized seed production of hybrid rice in Youxian, Hunan [J]. Hybrid Rice, 2024, 39(1): 88-92.

[32]

Guo L, Shu X, Zhu Y. Smart farming with swarm intelligence: hybrid algorithm for optimal multi drone plant protection paths [J]. Pakistan Journal of Agricultural Sciences, 2025, 62(2): 215-225.

[33]

Wang B, Du X, Wang Y, et al. Multi-machine collaboration realization conditions and precise and efficient production mode of intelligent agricultural machinery [J]. International Journal of Agricultural and Biological Engineering, 2024, 17(2): 27-36.

[34]

Hu P, Zhang R, Yang J, et al. Development status and key technologies of plant protection UAVs in China: a review [J]. Drones, 2022, 6(11): 354.

[35]

Li J, Ren W. A multi-machine cooperation full coverage path planning method in agriculture [C]// 2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT), IEEE, 2023: 713-716.

[36]

Zhou D. Swarm intelligence-based Multi-UAV cooperative coverage and path planning for precision pesticide spraying in irregular farmlands [C]// 2025 3rd International Conference on Artificial Intelligence and Automation Control (AIAC), IEEE, 2025: 395-398.

[37]

四川省农业农村厅．聚焦四大领域发力四川加快农业领域低空经济发展[EB/OL]．（2025-04-22）[2026-01-11]．https://nynct.sc.gov.cn/nynct/c100630/2025/4/22/af1aacfa257f453383051a339c7440d1.shtml.

[38]

Wang L, Lan Y, Zhang Y, et al. Applications and prospects of agricultural unmanned aerial vehicle obstacle avoidance technology in China [J]. Sensors, 2019, 19(3): 642.

[39]

Wang D, Li W, Liu X, et al. UAV environmental perception and autonomous obstacle avoidance: a deep learning and depth camera combined solution [J]. Computers and Electronics in Agriculture, 2020, 175: 105523.

[40]

Li J, Xiong X, Yan Y, et al. A survey of indoor uav obstacle avoidance research [J]. IEEE Access, 2023, 11: 51861-51891.

[41]

Wang Y, Jia W, Ou M, et al. A review of orchard canopy perception technologies for variable-rate spraying [J]. Sensors, 2025, 25(16): 4898.

[42]

四川省农业农村厅．宜宾市江安县统防统治力促高粱丰收[EB/OL]．（2025-07-18）[2025-12-15]．https://nynct.sc.gov.cn//nynct/c100632/2025/7/18/bf811227a11542589505065c0cbcb8f7.shtml.

[43]

四川省农业农村厅．乐山市峨边县“保卫”马铃薯无人机飞防尽显科技范[EB/OL]．（2024-05-07）[2025-11-05]．https://nynct.sc.gov.cn//nynct/c100632/2024/5/7/e2ea3ee629fe42ce8ef4e579ac72128c.shtml.

[44]

四川省农业农村厅．眉山市丹棱县：无人机飞防作业助力丹棱农业现代化[EB/OL]．（2020-06-10）[2025-11-05]．https://nynct.sc.gov.cn//nynct/c100632/2020/6/10/5926a29263a140a5a1e2675e1c89b3f8.shtml.

[45]

四川省农业农村厅．自贡市贡井区打出“病虫防控+灌溉保障+技术服务”组合拳力保水稻丰产丰收[EB/OL]．（2025-06-10）[2025-12-11]．https://nynct.sc.gov.cn//nynct/c100632/2025/6/10/c775191f343144d09647b646dfe3b3f8.shtml.

[46]

Liu Y, Feng H, Fan Y, et al. Utilizing UAV-based hyperspectral remote sensing combined with various agronomic traits to monitor potato growth and estimate yield [J]. Computers and Electronics in Agriculture, 2025, 231: 109984.

[47]

Yang X, Chen J, Lu X, et al. Advances in UAV remote sensing for monitoring crop water and nutrient status: modeling methods, influencing factors, and challenges [J]. Plants, 2025, 14(16): 2544.

[48]

Aziz D, Rafiq S, Saini P, et al. Remote sensing and artificial intelligence: revolutionizing pest management in agriculture [J]. Frontiers in Sustainable Food Systems, 2025, 9: 1551460.

[49]

Mpisane K, Kganyago M, Munghemezulu C, et al. A systematic review of remote sensing technologies and techniques for agricultural insect pest monitoring: lessons for locustana pardalina (Brown Locust) control in South Africa [J]. Frontiers in remote sensing, 2025, 6: 1571149.

[50]

Harani P, Gautam S, Joshi S K, et al. Advancements in soil moisture estimation through integration of remote sensing and artificial intelligence techniques [J]. Science of The Total Environment, 2025, 1001: 180503.

[51]

Montzka C, Brocca L, Chen H, et al. AI in soil moisture remote sensing [J]. International Journal of Applied Earth Observation and Geoinformation, 2025, 146: 105011.

[52]

Zhang C, Yi Y, Zhang S, et al. Quantitative analysis of vertical and temporal variations in the chlorophyll content of winter wheat leaves via proximal multispectral remote sensing and deep transfer learning [J]. Agriculture, 2024, 14(10): 1685.

[53]

李世隆，许辰一，王楠，等．基于BWO-ELM的水稻氮素无人机高光谱反演研究[J]．智能化农业装备学报（中英文），2024，5（3）：14-21.

Li Shilong, Xu Chenyi, Wang Nan, et al. Research on rice nitrogen unmanned aerial vehicle hyperspectral inversion based on BWO-ELM [J]. Journal of Intelligent Agricultural Mechanization, 2024, 5(3): 14-21.

[54]

马锃宏，岳佳文，殷程，等．基于不同拍摄角度多幅图像的果园视觉导航[J]．智能化农业装备学报（中英文），2024，5（4）：51-65.

Ma Zenghong, Yue Jiawen, Yin Cheng, et al. Visual navigation in orchard based on multiple images at different shooting angles [J]. Journal of Intelligent Agricultural Mechanization, 2024, 5(4): 51-65.

[55]

王天一，路梦源，贺刚，等．融合植被三维结构与光谱特征的草原地上生物量估算模型[J]．农业机械学报，2025，56（11）：76-83.

Wang Tianyi, Lu Mengyuan, He Gang, et al. Estimation model of grassland above ground biomass integrating three-dimensional structure and spectral characteristics of vegetation [J]. Transactions of the Chinese Society for Agricultural Machinery, 2025, 56(11): 76-83.

[56]

杜瑞麒．基于低空遥感数据和过程模型的冬油菜生长和水氮监测方法研究[D]．杨凌：西北农林科技大学，2024.

Du Ruiqi. Monitoring winter canola growth and water-nitrogen with low-altitude remote sensing and process-based model [D]. Yangling: Northwest A&F University, 2024.

[57]

江永成，吕蕴娴，胡根生．基于无人机遥感图像的茶叶枯病病斑半监督检测方法[J]．农业机械学报，2025，56（11）：441-452.

Jiang Yongcheng, Lü Yunxian, Hu Gensheng. Semi-supervised object detection method for spots of tea leaf blight based on UAV remote sensing images [J]. Transactions of the Chinese Society for Agricultural Machinery, 2025, 56(11): 441-452.

[58]

王铁山，黎丽莎．丘陵山区农业机械化发展困境与对策：以贵州省遵义市播州区为例[J]．农业工程，2022，12（10）：17-21.

Wang Tieshan, Li Lisha. Predicament and countermeasures of agricultural mechanization development in hills and mountainous areas taking Bozhou District, Zunyi City, Guizhou Province as an example [J]. Agricultural Engineering, 2022, 12(10): 17-21.

[59]

人民网．眉山市彭山区：柑橘“搭上”无人机科技助农庆丰收[EB/OL]．（2025-01-13）[2025-11-05]．http://sc.people.com.cn/n2/2025/0113/c407319-41106623.html.

[60]

西华大学．自主研发！西华大学大载重低空飞行平台亮相全国现场会！[EB/OL]．（2025-10-10）[2025-11-05]．https://mp.weixin.qq.com/s?__biz=MjM5MTAwODkwMA==&mid=2652618969&idx=1&sn=31d5860c9c7697e373620add592f8c45&chksm=bc8eb1bfbd1c9e43d32d7e70e195244e611f5ae64fe7fbcc49f64733236757660751a467d714&scene=27.

[61]

陶玥玥，黄萌，朱赟德，等．水田和旱地无人机飞播油菜适宜缓释肥用量[J]．农业工程学报，2025，41（2）：94-102.

Tao Yueyue, Huang Meng, Zhu Yunde, et al. Appropriate amount of the controlled-release fertilizer for aerial-sown rapeseed in paddy and upland field [J]. Transactions of the Chinese Society of Agricultural Engineering, 2025, 41(2): 94-102.

[62]

张青松，张恺，廖庆喜，等．油菜无人机飞播装置设计与试验[J]．农业工程学报，2020，36（14）：138-147.

Zhang Qingsong, Zhang Kai, Liao Qingxi, et al. Design and experiment of rapeseed aerial seeding device used for UAV [J]. Transactions of the Chinese Society of Agricultural Engineering, 2020, 36(14): 138-147.

[63]

四川省农业农村厅．无人机飞播油菜在成都温江区试飞成功[EB/OL]．（2020-10-16）[2025-11-05]．https://nynct.sc.gov.cn//nynct/c100632/2020/10/16/51681aaff64c49d29c608dc63fa109f6.shtml.

[64]

四川省农业农村厅．乐山市夹江县开启数字化种田模式激活农业新质生产力[EB/OL]．（2025-05-30）[2025-11-05]．http://nynct.sc.gov.cn//nynct/c100632/2025/5/30/df9f2d1658054ef19d3b351fdf62aa28.shtml.

[65]

四川省农业农村厅．绵阳三台植保无人机“飞”进稻田助农增收[EB/OL]．（2025-08-07）[2025-11-05]．http://nynct.sc.gov.cn/nynct/c100632/2025/8/7/d537aa3b187146b597cf231e66c5c2f2.shtml.

[66]

胡淑芬，曹昕奕，邓勇杰，等．植保无人机飞行参数对油茶授粉雾滴分布及坐果率的影响[J]．农业工程学报，2023，39（20）：92-100.

Hu Shufen, Cao Xinyi, Deng Yongjie, et al. Effects of the flight parameters of plant protection drone on the distribution of pollination droplets and the fruit setting rate of camellia [J]. Transactions of the Chinese Society of Agricultural Engineering, 2023, 39 (20): 92-100.

[67]

刘爱民，张海清，廖翠猛，等．单旋翼农用无人机辅助杂交水稻制种授粉效果研究[J]．杂交水稻，2016，31（6）：19-23.

Liu Aimin, Zhang Haiqing, Liao Cuimeng, et al. Effects of supplementary pollination by single-rotor agricultural unmanned aerial vehicle in hybrid rice seed production [J]. Hybrid Rice, 2016, 31(6): 19-23.

[68]

林金平，任万军，冯燕，等．机械育插秧和无人机技术在正优538制种中的应用[J]．种子，2020，39（8）：164-166.

Lin Jinping, Ren Wanjun, Feng Yan, et al. Application of mechanical transplanting and unmanned aerial vehicle(UAV) technology in the seed production of rice variety Zhengyou 538 [J]. Seed, 2020, 39(8): 164-166.

[69]

文民操，朱孔志，谭宜国，等．杂交水稻全程机械化制种技术在荃优607上的应用研究[J]．杂交水稻，2023，38（4）：109-113.

Wen Mincao, Zhu Kongzhi, Tan Yiguo, et al. Application of whole-process mechanized hybrid rice seed production technology in Quanyou 607 [J]. Hybrid Rice, 2023, 38(4): 109-113.

[70]

绵阳市农业农村局．无人机当“红娘”赶花授粉效率高[EB/OL]．（2024-07-23）[2026-01-11]．https://nyncj.my.gov.cn/mysnyncj/c101318/202407/a7747d9706a544948bb425d2d3525ea8.shtml.

[71]

陈进，吴瑕玉，王浩，等．无人机在四川水稻生产中的应用研究[J]．四川农业与农机，2025（1）：19-21.

[72]

Jozi S D. UAV-based post-disaster damage assessment of buildings using image processing [D]. Edmonton: University of Alberta, 2024.

[73]

四川省交通运输厅道路运输管理局．央视聚焦|邛崃：无人机寄递业务助力快递进村[EB/OL]．（2025-05-20）[2026-01-11]．https://jtt.sc.gov.cn/jtt/c102020/2025/5/20/497d585bd2554047b37c35c4892afb04.shtml.

[74]

太平洋科技．植保无人机续航怎么解决[EB/OL]．（2025-10-15）[2026-01-11]．https://www.pconline.com.cn/zhizao/1996/19964647.html.

[75]

Yang D, Liu H. 3D path optimization of UAV based on improved RRT algorithm and artificial potential field method [C]// 2024 7th International Conference on Mechatronics and Computer Technology Engineering(MCTE), Guangzhou, China, 2024: 789-792.

[76]

Ma X, Gong H, Liu Z, et al. Simulation research on dynamic UAV real-time obstacle avoidance based on interfered fluid dynamical system algorithm [C]// 2025 8th International Conference on Robotics, Control and Automation Engineering (RCAE), IEEE, 2025: 386-390.

[77]

Sheng J, Chai J, Geng R. Research on autonomous obstacle avoidance algorithm of forest fire reconnaissance UAV based on improved DWA algorithm [C]// 2025 5th International Conference on Artificial Intelligence, Big Data and Algorithms (CAIBDA), IEEE, 2025: 1616-1621.

[78]

Keyu L, Yonggen L, Yanchi Z. Dynamic obstacle avoidance path planning of UAV Based on improved APF[C]// 2020 5th International Conference on Communication, Image and Signal Processing (CCISP), IEEE, 2020: 159-163.

[79]

Chen R, Sun Y, Liang L, et al. Joint power allocation and placement scheme for UAV-assisted IoT with QoS guarantee [J]. IEEE Transactions on Vehicular Technology, 2021, 71(1): 1066-1071.

2026年第7卷第2期

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doi: 10.12398/j.issn.2096-7217.2026.02.004

接收时间：2026-01-14
首发时间：2026-11-05
出版时间：2026-05-15

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收稿日期：2026-01-14
修回日期：2026-03-09

基金

National Natural Science Foundation of China(U24A20141)

国家自然科学基金区域联合基金项目(U24A20141)

National Natural Science Foundation of China(32501805; 52102384)

国家自然科学基金项目(32501805; 52102384)

作者信息

^1.西华大学，四川成都，610039

^2.北京航空航天大学，北京市，100191

通讯作者:

^* 刘环宇，男，1990年生，黑龙江哈尔滨人，博士，副教授；研究方向为低空飞行农业装备、农机自主作业关键技术。E-mail：liuhy0528@163.com

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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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