Identifying Working Trajectories of the Wheat Harvester In-Field Based on K-Means Algorithm

Identifying the in-field trajectories of harvests is important for the activity analysis of agricultural machinery. This paper presents a K-means-based trajectory identification method that can automatically detect the “turning”, “working”, and “abnormal working” trajectories for wheat harvester in-...

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Bibliographic Details

Published in:	Agriculture
Main Authors:	Lili Yang, Xinxin Wang, Yuanbo Li, Zhongxiang Xie, Yuanyuan Xu, Rongxin Han, Caicong Wu
Format:	Article
Language:	English
Published:	MDPI AG 2022-11-01
Subjects:	agricultural machinery trajectory recognition k-means clustering machine learning GNSS data
Online Access:	https://www.mdpi.com/2077-0472/12/11/1837