Research on Intelligent Obstacle Avoidance Technology and Method for Underground Trackless Mining Equipment

Abstract: The three-dimensional obstacle avoidance and detection system is developed based on the analysis of the existing obstacle avoidance technology for trackless equipment． An intelligent obstacle avoidance and early warning method for trackless mining equipment in underground mine based on three-dimensional environment detection is pro- posed． The background of the technology is introduced and the roadway detection model is established，including the methods for transverse distance and longitudinal distance judgment． The method is applied to a LHD and the results show that the method has effectiveness and wide application prospects for unmanned LHD．

Keywords: underground mining; intelligent obstacle avoidance; trackless equipment; three-dimensional obstacle avoidance and detection system; graded early warning; radar

Introduction

With the development of intelligent and unmanned mining industry, the development of intelligent mining technology and equipment has become the only way for the mining industry. Intelligent mining equipment is the premise of intelligent mining. Intelligent obstacle avoidance is the key technology to realize the unmanned driving of trackless mining equipment, and is the core of improving the safe and efficient operation level of underground trackless mining equipment. It is urgent to develop intelligent obstacle avoidance technology. This paper proposes an intelligent obstacle avoidance and early warning method for trackless mining equipment in underground mine based on 3D environment detection, which can improve the accuracy of obstacle avoidance detection of mining equipment and greatly reduce the accident risk of underground trackless equipment operation.

1. Three Dimensional Obstacle Avoidance Detection System

The hardware of 3D obstacle avoidance detection system mainly includes core board, gyroscope, laser ranging sensor, motor, deceleration mechanism, encoder and motor controller, wireless router, battery and so on (see Figure 1).

Fig. 1 Composition of 3D Obstacle Avoidance Detection System

The two-dimensional laser ranging sensor is driven by the motor to rotate to realize the three-dimensional perception of the tunnel contour. The CPU collects the data of the line laser through the USB interface, and controls the operation of the motor at the same time; the azimuth information obtained by the gyroscope matches the point data collected by the line laser in real time, and then sends it to the handheld PDA through the Ethernet interface, which is the technical framework.

Fig. 2 Technical Framework of 3D Obstacle Avoidance Detection System

2. Research on Intelligent Obstacle Avoidance Technology

2.1 Establishment of Tunnel Detection Model

Firstly, the roadway environment is divided into six areas (up, down, front, back, left and right) according to the visual angle. Each area has a 90 ° angle of view to ensure the seamless and non overlapping coverage of the space (see Figure 3). The distribution of occupation probability map is counted in each perspective range. According to the distribution, the weight that can advance in this direction is calculated, and the direction with the largest weight is selected to carry out the advance; when the weight values are less than a certain value, it is determined that there is no moving direction, and the movement in this direction is prohibited.

Firstly, the roadway environment is divided into six areas (up, down, front, back, left and right) according to the visual angle. Each area has a 90 ° angle of view to ensure the seamless and non overlapping coverage of the space (see Figure 3). The distribution of occupation probability map is counted in each perspective range. According to the distribution, the weight that can advance in this direction is calculated, and the direction with the largest weight is selected to carry out the advance; when the weight values are less than a certain value, it is determined that there is no moving direction, and the movement in this direction is prohibited.

Fig. 3 Spatial Orientation Segmentation

2.2 Roadway Obstacle Avoidance Technology

In order to realize the obstacle avoidance of trackless mining equipment, it is necessary to install a three-dimensional obstacle avoidance detection system on the trackless equipment, collect the three-dimensional information of the roadway by using the lidar, so as to construct the three-dimensional perception form of the underground roadway, and evaluate the distance between the trackless equipment and the obstacles or the tunnel wall through the tunnel detection model, so as to realize the obstacle avoidance early warning.

Roadway 3D detection information is an important basis for judging the safe driving of trackless equipment. In order to accurately evaluate the safe driving trend of trackless equipment, the 3D space model of roadway is simplified and projected onto the plane, and the early warning evaluation is carried out through the two-dimensional plane distance. The linear distance obtained by lidar scanning is transformed into the two-dimensional coordinate information of the detection point. In the plane coordinate system, in order to obtain the two-dimensional coordinate information of the detection point, it is necessary to convert the linear distance into the transverse distance and longitudinal distance between the measurement point and the lidar. The transverse and longitudinal distance model is shown in Figure 4.

Fig. 4 Schematic Diagram of Horizontal and Vertical Distance Model

3. Conclusion

In this paper, an intelligent obstacle avoidance technology for trackless mining equipment is proposed, which can effectively restrict the running path of trackless equipment and avoid collision and collision accidents of trackless equipment in the process of driving by multi section classification early warning. The intelligent obstacle avoidance and early warning method of trackless mining equipment in underground mine based on three-dimensional environment detection can effectively reduce the accident risk of trackless equipment operation, improve the intelligent degree of trackless equipment, effectively reduce the probability of collision accidents, and improve the level of mine safety production, which has a wide application value.

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