To solve the problems of difficult pose measurement of tunneling equipment in low illumination, high dust and multi-light environment in coal mine, a visual positioning method of tunneling equipment based on the improved RANSAC feature extraction is proposed. Firstly, the three laser target images collected by the mine explosion-proof camera are preprocessed, and the shape and wire frame models are established respectively. Then, according to the shape model, the coordinate extremum is taken as the initial point of the elliptic model. The ratio of the difference between the previous and the latter two internal points is the optimal number of iterations, and the optimal parameters of the elliptic model are iteratively obtained to extract the point feature. According to the wireframe model, the pixel coordinate model is used as the initial point of the straight line model, and the line features are obtained by using the adaptive condition threshold and the sampling times. Finally, the point line feature is used as the input of the 3P3L pose solution model, and the pose information of the tunneling equipment is obtained by spatial coordinate transformation. Experimental results show that the relative error of the visual positioning method described in this artcle is ±45 mm within the range of 80 m from the three laser target, which can basically meet the positioning requirements of the coal mine tunneling equipment. It provides a new idea for the pose measurement of the tunneling equipment in the harsh environment of the coal mine.