Open Access
ARTICLE
An Adaptive Vision Navigation Algorithm in Agricultural IoT System for Smart Agricultural Robots
Zhibin Zhang1,2,*, Ping Li1,3, Shuailing Zhao1,2, Zhimin Lv1,2, Fang Du1,2, Yajian An1,2
1 School of Computer science, Inner Mongolia University, Hohhot, 010021, China
2 Key Laboratory of Wireless Networks and Mobile Computing, School of Computer Science, Inner Mongolia University, Hohhot, 010021, China
3 Simulation Center, Air Force Early Warning Academy, Wuhan, 430019, China
* Corresponding Author: Zhibin Zhang. Email:
Computers, Materials & Continua 2021, 66(1), 1043-1056. https://doi.org/10.32604/cmc.2020.012517
Received 02 July 2020; Accepted 14 September 2020; Issue published 30 October 2020
Abstract
As the agricultural internet of things (IoT) technology has evolved,
smart agricultural robots needs to have both flexibility and adaptability when
moving in complex field environments. In this paper, we propose the concept
of a vision-based navigation system for the agricultural IoT and a binocular vision
navigation algorithm for smart agricultural robots, which can fuse the edge contour and the height information of rows of crop in images to extract the navigation
parameters. First, the speeded-up robust feature (SURF) extracting and matching
algorithm is used to obtain featuring point pairs from the green crop row images
observed by the binocular parallel vision system. Then the confidence density
image is constructed by integrating the enhanced elevation image and the corresponding binarized crop row image, where the edge contour and the height information of crop row are fused to extract the navigation parameters (
θ,
d) based on
the model of a smart agricultural robot. Finally, the five navigation network
instruction sets are designed based on the navigation angle
θ and the lateral distance
d, which represent the basic movements for a certain type of smart agricultural robot working in a field. Simulated experimental results in the laboratory
show that the algorithm proposed in this study is effective with small turning
errors and low standard deviations, and can provide a valuable reference for
the further practical application of binocular vision navigation systems in smart
agricultural robots in the agricultural IoT system.
Keywords
Cite This Article
Z. Zhang, P. Li, S. Zhao, Z. Lv, F. Du
et al., "An adaptive vision navigation algorithm in agricultural iot system for smart agricultural robots,"
Computers, Materials & Continua, vol. 66, no.1, pp. 1043–1056, 2021. https://doi.org/10.32604/cmc.2020.012517
Citations