Research on Working Target Detection of Bulldozer Based on Binocular Vision
Mingchun Li, Quancheng Dong, Renpeng Xing, Shukun Cao, Xuan Sun, Changchun Ma · Journal of Physics Conference Series · 2021
Abstract Aiming at the problem of bad working environment of bulldozer in landfill, this paper presents a target detection method suitable for autonomous working bulldozer. Firstly, the working environment information was obtained by the binocular camera, the maximum inter-class variance method was used to remove the sky background by binarization of the image, and the color component of the ground was extracted from the HSV color space and converted into a binarization image. The absolute value of the difference between the two binarization images was the approximate area of the working target. Then the binocular camera was calibrated and the feature points were detected and matched in the target area. The parallax was obtained by triangulation principle to obtain the depth information of the target. The experimental results show that the method can correctly extract the depth information of the target area and target, and the accuracy is high, which can meet the requirements of the bulldozer in the landfill for target detection.