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Recognition of agricultural machinery operation trajectory based on BP_Adaboost

Yashuo Li, Weihao Fu, Xiaofeng Jia, Bo Zhao, Renzhong Su, Minghan Xu, Zaixi Pang, Yueru Zhang

Article ID: 2051
Vol 3, Issue 2, 2022

VIEWS - 44 (Abstract)

Abstract

The movement track of agricultural machinery includes not only the field operation track but also the road driving track. Effectively distinguish the operation tracks of field operation and road driving during the driving of agricultural machinery, accurately divide effective operation plots, and accurately evaluate the operation efficiency of agricultural machinery so as to realize remote intelligent management of agricultural machinery. Typical characteristic data was extracted by analyzing attributes of agricultural machinery trajectory points, and a training model established by the method of BP_AdaBoost was used to recognize track points of agricultural machinery. After remarking error-prone track points at the junction of road and field, it was trained again. The correct rate of track recognition was 96.89%. It not only avoided the dependence of traditional clustering algorithms on thresholds and parameters but also effectively solved the problem of mistaking road driving trajectory into field operation trajectory.

Keywords

agricultural machinery operation track; BP_Adaboost; clustering algorithm

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DOI: https://doi.org/10.54517/ama.v3i2.2051
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