Complicated Cavity Feature Recognition And Trajectory Planning Application For Robot Processing Of Cabin Parts

The integral cabin is a more critical part in aerospace equipment.The bulkhead is radially closed,the cavity on the inner wall has complex features,and the number of surfaces to be processed is large.The current programming and processing methods have low automation and efficiency.In response to these above problems,this paper has carried out the research on the automatic recognition of the whole cabin parts features and the robot processing trajectory planning of cabin parts,and developed the corresponding software function modules.Aiming at the shortcomings of the current programming methods of integral cabin parts that require human-computer interaction to manually select the machining surface,this paper studies the decomposition of the cavity intersecting features of cabin parts and the recognition of the machining area.Based on the graph feature method,a quick decomposition method of cavity features is realized.By searching for the suspected cavity surface,the concave adjacent edges of the cavity surface are directly decomposed,and the intersecting features with multiple islands are quickly decomposed into isolated features and then identified.Through the mapping method,the complex cavity on the regular surface of the cabin part is expanded into a plane complex cavity to simplify the identification and trajectory planning of the processing area,and the processing area is automatically identified through the ray nesting method.In the complex cavity trajectory planning of integral cabin parts,this paper studies the low-complexity complex cavity trajectory generation algorithm.Partition planning of complex cavities in the overall cabin section reduces the complexity and calculation amount of interference judgment and elimination.It is simple and effective to realize the correction offset method based on the angle bisector line segment to eliminate local interference.When the angle bisector is offset,the intersection point of the angle bisector is judged and local interference is eliminated.Generate trajectory of first line cutting and then circular cutting,optimize the tool lifting sequence,and verify that the one-way cutting and reciprocating milling trajectories after the optimization of the tool lifting sequence are shortened by 12.13%and 13.88%,tool lift optimization improves processing efficiency.According to the feature recognition technology and trajectory generation and optimization method in this paper,using C# and MATLAB hybrid programming technology,the overall interface of the robot intelligent processing software and the feature recognition and trajectory automatic generation module are developed.An energy consumption prediction model based on the feed direction of robot milling was established,and the accuracy of the model was verified by experiments to be 96.5%.The machining quality of robot milling in the feed direction of the least energy consumption was good.According to the energy consumption prediction model,the cutting and feeding direction of the cabin parts is selected as the horizontal direction.The operational performance of the robot intelligent processing software and the effect of the energy consumption prediction model are verified by the robot milling the cabin parts.