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A Farm Management Information System for Semi-Supervised Path Planning and Autonomous Vehicle Control

文献类型： 外文期刊

作者： Wang, Hao 1 ; Ren, Yaxin 3 ; Meng, Zhijun 1 ;

作者机构： 1.Beijing Acad Agr & Forestry Sci, Beijing Res Ctr Intelligent Equipment Agr, Beijing 100097, Peoples R China

2.Hokkaido Univ, Res Fac Agr, Sapporo, Hokkaido 0658589, Japan

3.Beijing Acad Agr & Forestry Sci, Beijing Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China

关键词： smart agriculture; image segmentation; agricultural robot; field registration

期刊名称：SUSTAINABILITY （ 影响因子：3.251； 五年影响因子：3.473 ）

ISSN：

年卷期： 2021 年 13 卷 13 期

页码：

收录情况： SCI

摘要： This paper presents a farm management information system targeting improvements in the ease of use and sustainability of robot farming systems. The system integrates the functionalities of field survey, path planning, monitoring, and controlling agricultural vehicles in real time. Firstly, a Grabcut-based semi-supervised field registration method is proposed for arable field detection from the orthoimage taken by the drone with an RGB camera. It partitions a complex field into simple geometric entities with simple user interaction. The average Mean Intersection over Union is about 0.95 when the field size ranges from 2.74 ha to 5.06 ha. In addition, a desktop software and a web application are developed as the entity of an FMIS. Compared to existing FMISs, this system provides more advanced features in robot farming, while providing simpler user interaction and better results. It allows clients to invoke web services and receive responses independent of programming language and platforms. Moreover, the system is compatible with other services, users, and devices following the open-source access protocol. We have evaluated the system by controlling 5 robot tractors with a 2 Hz communication frequency. The communication protocols will be publicly available to protentional users.

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