基于视觉的井下矿车自定位方法

Q1 Agricultural and Biological Sciences 农业机械学报 Pub Date : 2012-01-01 DOI:10.6041/J.ISSN.1000-1298.2012.01.005
Yu Meng, Li Liu, Fei Ma, Nan Gan, X. Fu
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引用次数: 1

摘要

提出了一种基于视觉的地下矿车地标自定位方法。首先在模拟隧道中设置多个人工地标,然后利用车载视觉传感器对其进行识别。通过视觉距离测量法计算出车辆与识别地标之间的距离后,最后根据三角剖分法计算出车辆的位置。在这种自定位方法中,路标采用高密度的1-D条形码交错2 of 5进行编码。每一个地标都具有明显的视觉特征,在地标数据库中都有唯一与之相对应的位置数据。根据针孔成像原理,根据编码区域的实际高度与图像中的高度之比计算地标与车辆的距离。实验结果表明,所提出的自定位方法具有较高的效率和精度,基本满足自动驾驶汽车的要求。
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Vision-based self-localization method for underground mining vehicle
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.
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来源期刊
农业机械学报
农业机械学报 Agricultural and Biological Sciences-Agricultural and Biological Sciences (all)
CiteScore
4.80
自引率
0.00%
发文量
15162
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