Research on Autonomous Robotic Grinding of Bogie Welds

The paper introduces a robot autonomous grinding system for EMU train bogie welds. This system combines visual recognition technology and offline programming technology to achieve vision-guided teaching-free function and greatly improves the intelligence and efficiency of grinding operations. The traditional grinding process often relies on manual teaching or simple programming, which is difficult to deal with complex situations such as workpiece size differences and positioning deviations. This system uses a 3D vision camera to perform high-precision scanning of bogie welds, obtain weld position and shape information in real time, and quickly match it with the preestablished offline programming model to automatically generate a grinding path suitable for the current workpiece. This process can realize the precise positioning and operation of the grinding robot without manual intervention, effectively solving the problems of insufficient precision and low efficiency in traditional grinding methods. Experimental verification shows that this system can significantly improve the polishing quality of EMU train bogie welds, providing strong support for the intelligent upgrading of the rail transit manufacturing industry.