基于遗传算法的农业移动机器人视觉导航方法

为了保证田间作业的农业移动机器人能够对作物行进行自动识别,并且对干扰环境具有一定的鲁棒性,采用基于遗传算法的面一带模型匹配视觉辨识方法直接对未经任何预处理的田间作物图像进行识别.通过人工图像和实际图像扫描,论证了该方法对作物行间识别的准确性和稳定性,以及对于包括干扰物等环境噪声的鲁棒性.经实际田间作物图像辨识,验证了该方法在实时控制中的有效性.

Visual Navigation Method Based on Genetic Algorithm for Agricultural Mobile Robots

In order to ensure recognizing crop row automatically with some robustness against noise environment and to confirm its possible intelligence for an agriculture mobile robot working in the fields, a crop row recognition method was presented by using genetic algorithm with surface-strip model to detect the crop row imaged in the gray scale image without any preprocessing. The accuracy and stability of the proposed visual recognition of crop raw with high robustness against noise such as sunlight condition varieties and obstacles were demonstrated by artificial image and real image scanning. The robustness of the method against environmental noises and the effectiveness of the method for real-time recognition have been verified by using real rural images.