Discrete-superposition mechanism of multiple constraints for robotic machining posture twin planning

Recently, robotic machining has been widely used in open surface machining of various complex components due to its advantages of multiple degrees of freedom, flexible posture, and configuration of sensing system. However, the complicated surface workpiece in key marine power components need to fully interact with the fluid medium and generate thrust in the service process. The design of energy-saving and high-efficient component increases the complexity of the surface profile, which causes the challenge of robotic machining posture planning in multi-constrained space. This work proposes a novel twin planning method in feasible solution space based on discrete-superposition mechanism of multiple constraints. Firstly, the hierarchical process and superposition mechanism of decoupled constraints are studied. Secondly, the posture representation and twin planning model is promoted by analyzing the influence of each discretization constraint on the robotic machining solution space. Finally, three sets of experiments are carried out on the machining of large-size Cu-alloys workpiece. Compared with the conventional method, the coupling effect of kinematics and performance constraints on the posture is further considered on the basis of geometric constraints, leading to the superior performance in stable cutting depth amplitude and surface roughness in robotic machining. The proposed discrete-superposition mechanism provides a theoretical basis and representation medium for a deeper understanding of robotic posture twin planning, which displays potential application in the machining of large-size surface components with high service performance under extremely constrained performance requirements.