基于视觉的地下矿用车辆自定位方法

Vision-based Self-localization Method for Underground Mining Vehicle

提出一种用于地下矿用车辆自定位的视觉路标定位法,在模拟巷道中摆放多个人工路标,通过车载视觉传感器寻找并识别路标,采用视觉测距方法计算车辆与路标之间的距离,最后依据三角定位原理推算出车辆所在位置。人工路标采用一维条码中密度较高的交叉25码编码,每个路标的视觉特征明显并且其编码在数据库中均有唯一的位置数据与之对应。视觉测距采用针孔成像模型,根据路标编码区实际高度与图像中编码高度的比例关系计算车辆到路标的距离。实验结果证明,提出的定位方法定位频率大于5 Hz,横、纵向定位误差分别小于110 mm和150 mm,基本能够达到车辆自主行驶的定位要求。

A vision-based self-localization method was proposed for underground mining vehicle by using landmarks.Firstly,several artificial landmarks were located in a simulating tunnel,and then a vision sensor in vehicle was used to find and recognize them.After the distances between the vehicle and the recognized landmarks were calculated by a visual distance measurement method,the location of the vehicle was computed according to triangulation finally.In this self-localization method,landmarks were encoded by interleaved 2 of 5,a type of 1-D barcode with high density.Each landmark has obvious visual feature and there is a unique corresponding location data to it in the landmark database.Distance between a landmark and the vehicle was calculated on the basis of the ratio of the coding area＇s actual height to its height in the image according to the pinhole imaging principle.Experimental results showed that the self-localization method suggested almost meets the requirement for autonomous driving vehicle because of its high efficiency and precision.