TY - EJOU
AU - Zhang, Zhibin
AU - Li, Ping
AU - Zhao, Shuailing
AU - Lv, Zhimin
AU - Du, Fang
AU - An, Yajian
TI - An Adaptive Vision Navigation Algorithm in Agricultural IoT System for Smart Agricultural Robots
T2 - Computers, Materials \& Continua
PY - 2021
VL - 66
IS - 1
SN - 1546-2226
AB - 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.
KW - Smart agriculture robot; 3D vision guidance; confidence density image; guidance information extraction; agriculture IoT
DO - 10.32604/cmc.2020.012517