Vision-based self-localization method for underground mining vehicle

Abstract

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.