CASIA OpenIR  > 脑图谱与类脑智能实验室
Delivery of pollen to forsythia flower pistils autonomously and precisely using a robot arm
Yang, Minghao1,2; Lyu, Hongchang1,2; Zhao, Yongjia3; Sun, Yangchang1,2; Pan, Hang1,7,8; Sun, Qi4; Chen, Jinlong5; Qiang, Baohua5; Yang, Hongbo6
Source PublicationCOMPUTERS AND ELECTRONICS IN AGRICULTURE
ISSN0168-1699
2023-11-01
Volume214Pages:13
Abstract

Autonomous pollination robots have received significant attention in recent years. It is expected that these robots will assist farmers in pollinating plants effectively. Despite employing various pollination methods, delivering pollen autonomously and precisely to pistils (the reproductive organs of flowers) remains a challenge. This is due to the small size of pistils, as well as difficulty in their rotation and orientation identification. Under this background, we present a novel method for detecting the orientation and area of the rotated pistil, known as PSTL_Orient, which we combine with servoing techniques and flower detection to develop an autonomous pollination robot. The experimental results demonstrate the superiority of our proposed PSTL_Orient in comparison to existing state-of-the-art methods in the detection of the orientation and rotation of pistil anchors. Additionally, the proposed pollination robot can achieve a 91.08 % accuracy in detecting flowers and an 86.19 % success rate in pollinating the small pistils of forsythia flowers. By being mounted on a ground vehicle, the proposed robotic arm system can help farmers in practical large-scale greenhouse environments.

KeywordPollination robot Flower detection Pistil identification Convolutional neural network (CNN)
DOI10.1016/j.compag.2023.108274
Indexed BySCI
Language英语
Funding ProjectNational Key Research & Development Program of China[2018AAA0102902] ; Guangxi Key Research and Development Program[AB21220038] ; Guangxi Key Research and Development Program[AB23026048] ; Science and Technology on Aerospace Flight Dynamics Laboratory[KGJ6142210210311] ; National Natural Science Foundation of China (NSFC)[61873269] ; Hebei Natural Science Foundation[L192005] ; Beijing Natural Science Foundation[2020GXNSFAA297061] ; Natural Science Foundation of Guangxi of China[2019GXNSFDA185006] ; Natural Science Foundation of Guangxi of China[2019GXNSFDA185007] ; Natural Science Foundation of Guangxi of China[J210012] ; [F2021205014]
Funding OrganizationNational Key Research & Development Program of China ; Guangxi Key Research and Development Program ; Science and Technology on Aerospace Flight Dynamics Laboratory ; National Natural Science Foundation of China (NSFC) ; Hebei Natural Science Foundation ; Beijing Natural Science Foundation ; Natural Science Foundation of Guangxi of China
WOS Research AreaAgriculture ; Computer Science
WOS SubjectAgriculture, Multidisciplinary ; Computer Science, Interdisciplinary Applications
WOS IDWOS:001098188200001
PublisherELSEVIER SCI LTD
Sub direction classification人工智能+农业
planning direction of the national heavy laboratory实体人工智能系统(软、硬件)
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Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/54461
Collection脑图谱与类脑智能实验室
Corresponding AuthorYang, Minghao; Zhao, Yongjia
Affiliation1.Chinese Acad Sci CASIA, Inst Automat, Res Ctr Brain Inspired Intelligence BII, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
3.Beihang Univ, State Key Lab Virtual Real Technol & Syst, Beijing 100191, Peoples R China
4.Zhejiang Sci Tech Univ, Sch Informat Engn, Hangzhou 310018, Zhejiang, Peoples R China
5.Guilin Univ Elect Sci & Technol, Guilin 541004, Guangxi, Peoples R China
6.Beijing Informat Sci & Technol Univ, Beijing 100096, Peoples R China
7.Beihang Univ, Jiangxi Res Inst, Nanchang 330096, Jiangxi, Peoples R China
8.Changzhi Univ, Dept Comp Sci, Changzhi 046011, Peoples R China
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Yang, Minghao,Lyu, Hongchang,Zhao, Yongjia,et al. Delivery of pollen to forsythia flower pistils autonomously and precisely using a robot arm[J]. COMPUTERS AND ELECTRONICS IN AGRICULTURE,2023,214:13.
APA Yang, Minghao.,Lyu, Hongchang.,Zhao, Yongjia.,Sun, Yangchang.,Pan, Hang.,...&Yang, Hongbo.(2023).Delivery of pollen to forsythia flower pistils autonomously and precisely using a robot arm.COMPUTERS AND ELECTRONICS IN AGRICULTURE,214,13.
MLA Yang, Minghao,et al."Delivery of pollen to forsythia flower pistils autonomously and precisely using a robot arm".COMPUTERS AND ELECTRONICS IN AGRICULTURE 214(2023):13.
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