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Improved random sampling consensus algorithm for vision navigation of intelligent harvester robot

Bin Li (Beijing Research Center of Intelligent Equipment for Agriculture, Beijing, China)
Yu Yang (School of Instrument Science and Engineering, Southeast University, Nanjing, China)
Chengshuai Qin (School of Instrument Science and Engineering, Southeast University, Nanjing, China)
Xiao Bai (Department of Big Data, Efrei Paris, Paris, France)
Lihui Wang (School of Instrument Science and Engineering China, Southeast University, Nanjing, China)

Industrial Robot

ISSN: 0143-991x

Article publication date: 10 August 2020

Issue publication date: 9 October 2020

202

Abstract

Purpose

Focusing on the problem that the visual detection algorithm of navigation path line in intelligent harvester robot is susceptible to interference and low accuracy, a navigation path detection algorithm based on improved random sampling consensus is proposed.

Design/methodology/approach

First, inverse perspective mapping was applied to the original images of rice or wheat to restore the three-dimensional spatial geometric relationship between rice or wheat rows. Second, set the target region and enhance the image to highlight the difference between harvested and unharvested rice or wheat regions. Median filter is used to remove the intercrop gap interference and improve the anti-interference ability of rice or wheat image segmentation. The third step is to apply the method of maximum variance to thresholding the rice or wheat images in the operation area. The image is further segmented with the single-point region growth, and the harvesting boundary corner is detected to improve the accuracy of the harvesting boundary recognition. Finally, fitting the harvesting boundary corner point as the navigation path line improves the real-time performance of crop image processing.

Findings

The experimental results demonstrate that the improved random sampling consensus with an average success rate of 94.6% has higher reliability than the least square method, probabilistic Hough and traditional random sampling consensus detection. It can extract the navigation line of the intelligent combine robot in real time at an average speed of 57.1 ms/frame.

Originality/value

In the precision agriculture technology, the accurate identification of the navigation path of the intelligent combine robot is the key to realize accurate positioning. In the vision navigation system of harvester, the extraction of navigation line is its core and key, which determines the speed and precision of navigation.

Keywords

Acknowledgements

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

Citation

Li, B., Yang, Y., Qin, C., Bai, X. and Wang, L. (2020), "Improved random sampling consensus algorithm for vision navigation of intelligent harvester robot", Industrial Robot, Vol. 47 No. 6, pp. 881-887. https://doi.org/10.1108/IR-03-2020-0055

Publisher

:

Emerald Publishing Limited

Copyright © 2020, Emerald Publishing Limited

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