Design of Tan Sheep intelligent feeding navigation system based on RTK and deep learning

被引：0

作者：

Mao Jiandong ^{[1
,2
]}

Chen Xiongjie ^{[1
,2
]}

Yu Zetao ^{[1
,2
]}

机构：

[1] North Minzu Univ, Sch Elect & Informat Engn, Yinchuan 750021, Ningxia, Peoples R China

[2] Key Lab Atmospher Environm Remote Sensing Ningx, Yinchuan 750021, Ningxia, Peoples R China

来源：

2023 35TH CHINESE CONTROL AND DECISION CONFERENCE, CCDC | 2023年

关键词：

RTK navigation; deep learning; YOLO; obstacle detection; multi-sensor fusion;

D O I：

10.1109/CCDC58219.2023.10327154

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

An driverless feeding cart is designed for the roblems of high cost and low efficiency of manual feeding in m gxia Tan sheep breeding process. In this paper, GPS-BeiDou RTK navigation technology is used. The feeding cart mobile station receives GPS satellite signals and reference station signals, and locates the current position of the feeding cart with centimeter -level accuracy through real-time carrier phase difference technology, while combining deep learning YOLO vision algorithm to assist RTK navigation. By training a large number of relevant obstacle datasets from Tan sheep farms, the vision system achieves the effect of being able to recognize specific catepries of obstacles, thus achieving obstacle avoidance of the feed cart. In addition, if the RTK navigates the feed cart in an area where the GPS positioning signal is unstable, deep learning can be used to navigate through visual label localization combined with multi -sensor fusion techniques.

引用

页码：1425 / 1430

页数：6

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