Smooth and collision-free trajectory planning for redundant 3D laser cutting machines

Smooth and collision-free trajectory planning is crucial to high speed and high precision machining, such as 3D laser cutting. However, it is difficult to further enhance the kinematic performance of the primary translational axes during the process. This paper presents a novel two-phase planning strategy, which optimizes the tool orientation and leverages a redundant standoff axis to significantly enhance the smoothness of the translational movements in redundant 3D laser cutting machines. In the first phase, collision-free configuration spaces (C-spaces) are constructed along the tool path, utilizing a graph-based search approach with Dijkstra's algorithm for tool orientation optimization. Subsequently, a secondary orientation curve, namely the M path, is planned in the second phase with a variable distance from the primary tool path curve, and the motion of the redundant standoff axis is handled via a deep reinforcement learning approach. The proposed methodology provides an advancement in conventional five-axis machines lacking of flexibility. Experimental validation confirms the potential of the approach to substantially improve machining accuracy and efficiency.