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An improved particle filtering to locate the crop boundary of an unharvested region using vision

Lihui Wang (Southeast University, Nanjing, China)
Chengshuai Qin (Southeast University, Nanjing, China)
Yaoming Li (Jiangsu University, Zhenjiang, China)
Jin Chen (School of Mechanical Engineering, Jiangsu University, Zhenjiang, China)
Lizhang Xu (Jiangsu University, Zhenjiang, China)

Industrial Robot

ISSN: 0143-991x

Article publication date: 20 October 2020

Issue publication date: 5 July 2021

128

Abstract

Purpose

Accurately, positioning is a fundamental requirement for vision measurement systems. The calculation of the harvesting width can not only help farmers adjust the direction of the intelligent harvesting robot in time but also provide data support for future unmanned vehicles.

Design/methodology/approach

To make the length of each pixel equal, the image is restored to the aerial view in the world coordinate system. To solve the problem of too much calculation caused by too many particles, a certain number of particles are scattered near the crop boundary and the distribution regularities of particles’ weight are analyzed. Based on the analysis, a novel boundary positioning method is presented. In the meantime, to improve the robustness of the algorithm, the back-projection algorithm is also used for boundary positioning.

Findings

Experiments demonstrate that the proposed method could well meet the precision and real-time requirements with the measurement error within 55 mm.

Originality/value

In visual target tracking, using particle filtering, a rectangular is used to track the target and cannot obtain the boundary information. This paper studied the distribution of the particle set near the crop boundary and proposed an improved particle filtering algorithm. In the algorithm, a small amount of particles is used to determine the crop boundary and accurate positioning of the crop boundary is realized.

Keywords

Acknowledgements

The work was supported by Primary Research & Development Plan of Jiangsu Province [BE2018384], National Key Research and Development Program [2016YFD0702000], National Natural Science Foundation of China [61773113, 51875260].

Citation

Wang, L., Qin, C., Li, Y., Chen, J. and Xu, L. (2021), "An improved particle filtering to locate the crop boundary of an unharvested region using vision", Industrial Robot, Vol. 48 No. 2, pp. 211-220. https://doi.org/10.1108/IR-07-2020-0148

Publisher

:

Emerald Publishing Limited

Copyright © 2020, Emerald Publishing Limited

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