Visual row detection using pixel-based algorithm and stereo camera for cotton-picking robot
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Date
2019
Journal Title
Journal ISSN
Volume Title
Publisher
2019 ASABE Annual International Meeting, Boston, Massachusetts
Abstract
Precision farming still depends heavily on RTK-GPS to navigate the rows of crops. However, GPS cannot be the
only method to navigate the farm for robots to work as a “swarm” on the same farm; they also require visual systems
to navigate and avoid collisions. Also, plant growth and canopy changes are not accommodated. Hence, the visual
system remains a complementary method to add to the efficiency of the GPS system. In this study, optical detection
of cotton rows is investigated and demonstrated. A stereo camera is used to detect the row depth, and then, a pixel-
based algorithm is used to calculate and determine the upper and lower part of the canopy of the cotton rows by
assuming the normal distribution of the high and low pixels. The left and right row are detected by using perspective
transform and pixel-based sliding window algorithms. Then, the system determines the Bayesian score of the
detection and calculates the center of the rows for smooth navigation of the cotton-picking robot. The 92.3%
accuracy and F1 score of 0.951 are sufficient to deploy the algorithm for robotic operations. The deployment and
testing of the robot navigation will be done in 2019.
Description
Conference Paper
Keywords
GPS system, RTK-GPS, Precision farming, robotic cotton harvesting