Drip-Tape-Following Approach Based on Machine Vision for a Two-Wheeled Robot Trailer in Strip Farming

Due to the complex environment in field, using machine vision technology enable robot travel autonomously was a challenging task. This study investigates method based on mathematical morphology and Hough transformation for drip tape following by two-wheeled trailer. First, an image processing technique utilized extract image, including selection of region interest (ROI), Red-Green-Blue (RGB) Hue-Saturation-Value (HSV) color space conversion, channel selection, Otsu’s binarization, morphological operations. The line segments were obtained from extracted tapes transform operation. Next, deviation angle between segment vertical center estimated through two-dimensional law cosines. steering control system could adjust rotation speed left right wheels reduce angle, so that stably along tape, turning. guiding performance evaluated test path formed field. experimental results show proposed achieve average detection rate 97.3% lateral error 2.6 ± 1.1 cm, which superior other drip-tape-following methods combined with edge detection, such as Canny Laplacian.