Gradient and curve passing method for unmanned rail electric locomotive in deep limited space

Abstract

The invention discloses a slope and curve passing method for an unmanned tramcar in a deep limited space, and the method comprises the steps: enabling the tramcar to move in an underground roadway at a constant speed, collecting the road data in a moving process in real time through a solid-state laser radar, and feeding back the road data to an industrial control computer, thereby obtaining an original three-dimensional point cloud data package and imu data; segmenting ground point cloud data and non-ground point cloud data by using an RANSAC (Random Sample Consensus) algorithm; according to the collected imu data, the current pose of the solid-state laser radar is calculated and used for feeding back whether the electric locomotive runs on a slope or not, then the uphill and downhill lengths and positions are obtained, the accelerator of the electric locomotive is increased during uphill, the accelerator of the electric locomotive is reduced during downhill, and it is guaranteed that the electric locomotive runs normally at a constant speed; and judging whether the roadway wall is a curve or not according to the shape of the roadway wall, and calculating the curvature of the curve and the position of the curve. Therefore, the unmanned rail electric locomotive can accurately identify uphill, downhill and curves, so that the unmanned rail electric locomotive can smoothly pass under a mine.

Description

technical field [0001] The invention relates to an environment perception method for an unmanned vehicle, in particular to a method for the gradient and curve passage of an unmanned rail electric vehicle in a deep restricted space. Background technique [0002] Coal mine auxiliary transportation is an important part of the mine production system, which undertakes the transportation tasks of personnel, equipment and materials. Auxiliary transportation is divided into rail transportation and trackless transportation. In some mining areas, the geological structure is extremely complex, the section of the roadway is small, and the advancing length of the coal mining face is short, generally 400-600m; the coal mining face is replaced many times a year in a mining area, and the auxiliary transportation line is extended or migrated frequently with the work site; The surrounding rock is mostly composite soft rock, and the roof of the roadway is broken and falling, and the floor is ...

AI Technical Summary

Problems solved by technology

Nowadays, the main research direction of environment-aware obstacle-avoidance traffic at home and abroad is in the highway environment and urban road environment, and the slope and curve traffic in the special environment of the mine have been rarely mentioned so far.

And compared with the ground road, the structure of the underground roadway is complicated, the up and down slope is relatively large, and it is narrow and curved, which makes it very difficult to pass smoothly in the environment of the underground roadway, which is time-consuming and labor-intensive.

The existing method generally uses lidar and camera fusion perception on tram cars, but this method is complex to process data, increasing the amount of calculation, and the illumination of underground roadways is low, and it is difficult for cameras to restore the real environment, resulting in no one. When a rail vehicle encounters an uphill or downhill or a curve, it is misjudged as an obstacle to stop, or because the uphill or downhill or curve is not detected, the vehicle speed is too fast and derails when passing through the uphill or downhill, so how to provide a It is one of the research directions of this industry to make unmanned electric locomotives accurately identify uphill and downhill and curves, so as to ensure the smooth passage of unmanned electric locomotives in mines.

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