Gong-kuang zidonghua (Jun 2022)
Research on unmanned driving system of underground trackless rubber-tyred vehicle in coal mine
Abstract
The unmanned driving of underground trackless rubber-tyred vehicles in coal mine can significantly reduce the number of underground auxiliary transportation operating personnel, and reduce labor intensity. It is one of the leading development directions of intelligent auxiliary transportation. Compared with the unmanned driving of the ground vehicles, there are a series of new challenges for unmanned driving of underground trackless rubber-tyred vehicles. There is the interference of 'corridor effect' and 'multipath effect' in the underground roadway. There are high requirements for precise vehicle control under complex road conditions such as mixed traffic in narrow scenes. The underground satellite refusal environment causes positioning problems. Machine vision application is affected by the changeable illumination underground and the blocking of the roadway wall. The equipment shall meet MA certification. Multiple redundancy design is required for safety measures. In order to solve the above challenges, the architecture of the unmanned driving system for underground trackless rubber-tyred vehicle in coal mine based on the vehicle-to-everything is proposed. And the critical technologies of system implementation are analyzed. The integrated positioning method based on simultaneous localization and mapping (SLAM) and ultra wide band (UWB)/inertial navigation system (INS) is used to realize the precise positioning of the vehicle in the state of high-speed movement. By relying on the multi-sensor (millimeter-wave radar, laser radar, ultrasonic radar, camera) of the vehicle body and mining intelligent roadside unit, the road condition information around the vehicle body is identified. Through the vehicle-to-everything, the relevant information is shared. The multi-source data acquisition technology is used to obtain environmental perception data, vehicle operation data, roadside monitoring data, and mobile target data. The massive data is exchanged through 5G and other wireless communication networks to the distributed computing unit based on edge computing for fusion analysis. The vehicle driving path is reasonably planned in combination with global and local path planning algorithms to realize the systematic vehicle intelligent scheduling of warehouse management. Considering the safety access requirements of underground electromechanical equipment, the perception, wire control and decision-making control equipment shall be designed for mining. The mining intrinsically safe products shall be used as far as possible to meet the design requirements of low cost, small volume and high efficiency. Underground unmanned driving vehicles need to realize the redundant design of perception, decision-making and control links to realize the safe and reliable control of vehicles under abnormal conditions. The field test results show that the vehicle positioning precision can reach 0.3 m. The communication bandwidth is more than or equal to 50 Mbit/s. The data communication delay is less than or equal to 50 ms. Therefore the positioning precision and data exchange can meet the basic requirements of underground unmanned driving vehicles. The obstacle avoidance and continuous path planning can be realized for typical environments such as T-shaped roadway and U-shaped curve. Based on the multi-sensor fusion strategy, the perception capability of multiple targets can be improved. The vehicle dynamic following error is less than 0.54 m/s, and the average control error perpendicular to the roadway wall is less than 0.2 m. These results meet the control requirements of unmanned driving vehicles.
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