基于视觉的驾驶机器人导航技术

对驾驶机器人的视觉导航技术进行了研究,提出了一种快速可靠的车辆引导线检测算法.该算法首先对感兴趣的移动窗口进行有条件的边缘检测,进而引入了梯度方向直方图的处理思想,制定了车辆引导线边缘候选点集与有效点集的筛选算法,最后,通过所提出的一种基于标量化处理Kalman滤波方法实现了引导线特征参数的快速准确提取.试验表明,本文提出的检测算法能够满足复杂路况下的导航需要,具有30ms/帧的实时处理速度.

Navigation Technology of Driving Robot Based on Machine Vision

The navigation technology based on machine vision for driving robot in vehicle road tests is studied, A quick and robust image algorithm to detect vehicle inductive lines is proposed. In this algorithm, the conditional edge detection is carried out firstly within an interested mobile region. Then, a novel processing idea of gradient direction histogram is introduced. And how to select Candidate point sets and valid point sets on the inductive line edges is ascertained. Finally, the feature parameters about vehicle inductive lines are extracted quickly and accurately by the proposed Kalman filter with the scalar measurement processing. Experiments show that the proposed detection algorithm can satisfy the navigation demands of the driving robot even in the complex road environment and has the real-time processing velocity as quick as 30ms per frame.